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stringlengths 362
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stringlengths 2.11k
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int64 128
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|---|---|---|---|---|
Table InputTable: [["Rank", "Cyclist", "Team", "Time", "UCI ProTour\\nPoints"], ["2", "Alexandr Kolobnev (RUS)", "Team CSC Saxo Bank", "s.t.", "30"], ["1", "Alejandro Valverde (ESP)", "Caisse d'Epargne", "5h 29' 10\"", "40"], ["6", "Denis Menchov (RUS)", "Rabobank", "s.t.", "11"], ["5", "Franco Pellizotti (ITA)", "Liquigas", "s.t.", "15"], ["10", "David Moncoutié (FRA)", "Cofidis", "+ 2\"", "1"], ["7", "Samuel Sánchez (ESP)", "Euskaltel-Euskadi", "s.t.", "7"], ["8", "Stéphane Goubert (FRA)", "Ag2r-La Mondiale", "+ 2\"", "5"], ["3", "Davide Rebellin (ITA)", "Gerolsteiner", "s.t.", "25"], ["4", "Paolo Bettini (ITA)", "Quick Step", "s.t.", "20"], ["9", "Haimar Zubeldia (ESP)", "Euskaltel-Euskadi", "+ 2\"", "3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country had the most cyclists finish within the top 10?
|
Italy
|
Answer:
| 128
|
Table InputTable: [["Description Losses", "1939/40", "1940/41", "1941/42", "1942/43", "1943/44", "1944/45", "Total"], ["Deaths other countries", "", "", "", "", "", "", "2,000"], ["Deaths In Prisons & Camps", "69,000", "210,000", "220,000", "266,000", "381,000", "", "1,146,000"], ["Murdered in Eastern Regions", "", "", "", "", "", "100,000", "100,000"], ["Murdered", "75,000", "100,000", "116,000", "133,000", "82,000", "", "506,000"], ["Deaths Outside of Prisons & Camps", "", "42,000", "71,000", "142,000", "218,000", "", "473,000"], ["Direct War Losses", "360,000", "", "", "", "", "183,000", "543,000"], ["Total", "504,000", "352,000", "407,000", "541,000", "681,000", "270,000", "2,770,000"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many people were murdered in 1940/41?
|
100,000
|
Answer:
| 128
|
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs", "National Cup"], ["1936/37", "N/A", "ASL", "5th, National", "Did not qualify", "Champion"], ["1935/36", "N/A", "ASL", "1st", "Champion (no playoff)", "?"], ["1937/38", "N/A", "ASL", "3rd(t), National", "1st Round", "?"], ["1953/54", "N/A", "ASL", "1st", "Champion (no playoff)", "Champion"], ["1933/34", "N/A", "ASL", "2nd", "No playoff", "?"], ["1934/35", "N/A", "ASL", "2nd", "No playoff", "?"], ["1942/43", "N/A", "ASL", "6th", "No playoff", "?"], ["1954/55", "N/A", "ASL", "8th", "No playoff", "?"], ["1943/44", "N/A", "ASL", "9th", "No playoff", "?"], ["1944/45", "N/A", "ASL", "9th", "No playoff", "?"], ["1931", "1", "ASL", "6th (Fall)", "No playoff", "N/A"], ["1939/40", "N/A", "ASL", "4th", "No playoff", "?"], ["1946/47", "N/A", "ASL", "6th", "No playoff", "?"], ["1955/56", "N/A", "ASL", "6th", "No playoff", "?"], ["1952/53", "N/A", "ASL", "6th", "No playoff", "Semifinals"], ["1950/51", "N/A", "ASL", "5th", "No playoff", "?"], ["1940/41", "N/A", "ASL", "6th", "No playoff", "?"], ["1945/46", "N/A", "ASL", "5th", "No playoff", "?"], ["1947/48", "N/A", "ASL", "6th", "No playoff", "?"], ["1938/39", "N/A", "ASL", "4th, National", "Did not qualify", "?"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did it take for the new york americans to win the national cup after 1936?
|
17 years
|
Answer:
| 128
|
Table InputTable: [["Series #", "Season #", "Title", "Notes", "Original air date"], ["11", "1", "\"Alfie's Birthday Party\"", "Goo and Melanie pretend they are dating and they leave Alfie out of everything. He ends up bored and starts hanging out with Dee Dee and his friends. However, it just isn't the same without Goo. Later on, Alfie learns about the surprise birthday party that Goo and Melanie had been planning with everyone else (except for Dee Dee, who couldn't know since he would've told).", "January 19, 1995"], ["10", "1", "'\"Donnell's Birthday Party\"", "Donnell is having a birthday party and brags about all the dancing and cool people who will be there. Harry says that he knows how to dance so Dee Dee feels left out because he doesn't know how to dance. Later on, Harry admits to Dee Dee alone that he can't dance either and only lied so he doesn't get teased by Donnell. So, they ask Alfie to help them learn how to dance. He refuses to help because Dee Dee previously told on him to Roger about his and Goo's plans to cheat on their math quiz. Alfie eventually agrees, after Melanie threatens to refuse to help him with his math homework. Soon Dee Dee and Harry learn Donnell's secret and were forced to teach him how to dance. After the party, Dee Dee tells Alfie about it and finds out that he knew Donnell was a liar.", "January 5, 1995"], ["7", "1", "\"Dee Dee's Girlfriend\"", "A girl kisses Dee Dee in front of Harry and Donnell. They promise not to tell, but it slips and everyone laughs at Dee Dee. Dee Dee ends his friendship with Harry and Donnell and hangs out with Alfie and Goo. Soon, Alfie and Goo finally get the three to talk to each other.", "December 15, 1994"], ["2", "1", "\"The Practical Joke War\"", "Alfie and Goo unleash harsh practical jokes on Dee Dee and his friends. Dee Dee, Harry and Donnel retaliate by pulling a practical joke on Alfie with the trick gum. After Alfie and Goo get even with Dee Dee and his friends, Melanie and Deonne help them get even. Soon, Alfie and Goo declare a practical joke war on Melanie, Dee Dee and their friends. This eventually stops when Roger and Jennifer end up on the wrong end of the practical joke war after being announced as the winner of a magazine contest for Best Family Of The Year. They set their children straight for their behavior and will have a talk with their friends' parents as well.", "October 22, 1994"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:alfie's birthday party aired on january 19. what was the airdate of the next episode?
|
January 26, 1995
|
Answer:
| 128
|
Table InputTable: [["Date", "Competition", "Location", "Country", "Event", "Placing", "Rider", "Nationality"], ["1 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "500 m time trial", "1", "Victoria Pendleton", "GBR"], ["1 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Jason Kenny", "GBR"], ["2 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Ross Edgar", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Ross Edgar", "GBR"], ["2 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jamie Staff", "GBR"], ["31 October 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Victoria Pendleton", "GBR"], ["2 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jason Kenny", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Chris Hoy", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jamie Staff", "GBR"], ["13 February 2009", "2008–09 World Cup", "Copenhagen", "Denmark", "Team sprint", "1", "Chris Hoy", "GBR"], ["30 October 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Chris Hoy", "GBR"], ["2 November 2008", "5th International Keirin Event", "Manchester", "United Kingdom", "International keirin", "2", "Ross Edgar", "GBR"], ["13 February 2009", "2008–09 World Cup", "Copenhagen", "Denmark", "Team sprint", "1", "Jason Kenny", "GBR"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of 1st place finishes across all events?
|
17
|
Answer:
| 128
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2006", "Commonwealth Games", "Melbourne, Australia", "7th", "Shot put", "18.44 m"], ["2006", "Commonwealth Games", "Melbourne, Australia", "4th", "Discus throw", "60.99 m"], ["2004", "African Championships", "Brazzaville, Republic of the Congo", "2nd", "Discus throw", "63.50 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "5th", "Shot put", "17.76 m"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "2nd", "Discus throw", "56.98 m"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "Discus throw", "59.51 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "2nd", "Discus throw", "62.86 m"], ["2007", "All-Africa Games", "Algiers, Algeria", "3rd", "Discus throw", "57.79 m"], ["2004", "Olympic Games", "Athens, Greece", "8th", "Discus throw", "62.58 m"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in which competition did hopley finish fist?
|
World Junior Championships
|
Answer:
| 128
|
Table InputTable: [["Year", "Film", "Role", "Language", "Notes"], ["2012", "Sagar", "Kajal", "Kannada", ""], ["2010", "Gaana Bajaana", "Radhey", "Kannada", ""], ["2013", "Dilwala", "Preethi", "Kannada", ""], ["2013", "Kaddipudi", "Uma", "Kannada", ""], ["2008", "Moggina Manasu", "Chanchala", "Kannada", "Filmfare Award for Best Actress - Kannada\\nKarnataka State Film Award for Best Actress"], ["2012", "18th Cross", "Punya", "Kannada", ""], ["2012", "Alemari", "Neeli", "Kannada", ""], ["2012", "Drama", "Nandini", "Kannada", ""], ["2012", "Addhuri", "Poorna", "Kannada", "Udaya Award for Best Actress\\nNominated — SIIMA Award for Best Actress\\nNominated — Filmfare Award for Best Actress – Kannada"], ["2013", "Bahaddoor", "Anjali", "Kannada", "Filming"], ["2010", "Krishnan Love Story", "Geetha", "Kannada", "Filmfare Award for Best Actress - Kannada\\nUdaya Award for Best Actress"], ["2011", "Hudugaru", "Gayithri", "Kannada", "Nominated, Filmfare Award for Best Actress – Kannada"], ["2012", "Breaking News", "Shraddha", "Kannada", ""], ["2009", "Love Guru", "Kushi", "Kannada", "Filmfare Award for Best Actress - Kannada"], ["2009", "Olave Jeevana Lekkachaara", "Rukmini", "Kannada", "Innovative Film Award for Best Actress"], ["2014", "Endendigu", "", "", "Filming"], ["2014", "Mr. & Mrs. Ramachari", "", "", "Announced"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of films with the language of kannada listed?
|
15
|
Answer:
| 128
|
Table InputTable: [["Game", "Day", "Date", "Kickoff", "Opponent", "Results\\nScore", "Results\\nRecord", "Location", "Attendance"], ["2", "Sunday", "November 17", "1:05pm", "Monterrey Flash", "L 6–10", "0–2", "UniSantos Park", "363"], ["15", "Saturday", "February 8", "7:05pm", "at Sacramento Surge", "W 10–6", "8–7", "Estadio Azteca Soccer Arena", "323"], ["5", "Saturday", "December 14", "7:05pm", "at Sacramento Surge", "W 7–6 (OT)", "3–2", "Estadio Azteca Soccer Arena", "215"], ["1", "Sunday", "November 10", "3:05pm", "at Las Vegas Legends", "L 3–7", "0–1", "Orleans Arena", "1,836"], ["13", "Saturday", "February 1", "7:05pm", "at San Diego Sockers", "L 5–6", "7–6", "Valley View Casino Center", "4,954"], ["12", "Sunday", "January 26", "1:05pm", "Sacramento Surge", "W 20–6", "7–5", "UniSantos Park", "224"], ["10", "Sunday", "January 12", "1:05pm", "Las Vegas Legends", "W 10–7", "5–5", "UniSantos Park", "343"], ["8", "Saturday", "January 4", "7:05pm", "at Ontario Fury", "L 5–12", "4–4", "Citizens Business Bank Arena", "2,653"], ["9", "Sunday", "January 5", "1:05pm", "San Diego Sockers", "L 7–12", "4–5", "UniSantos Park", "388"], ["16", "Saturday", "February 15♥", "5:05pm", "Bay Area Rosal", "W 27–2", "9–7", "UniSantos Park", "118"], ["3", "Saturday", "November 23", "7:05pm", "at Bay Area Rosal", "W 10–7", "1–2", "Cabernet Indoor Sports", "652"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the number of people attending the toros mexico vs. monterrey flash game?
|
363
|
Answer:
| 128
|
Table InputTable: [["Year", "Kit Manufacturer", "Shirt Sponsor", "Back of Shirt Sponsor", "Short Sponsor"], ["1977–1978", "", "National Express", "", ""], ["1995–1996", "Matchwinner", "Empress", "", ""], ["1982–1985", "Umbro", "", "", ""], ["1994–1995", "Klūb Sport", "Empress", "", ""], ["1993–1994", "Club Sport", "Gulf Oil", "", ""], ["1986–1988", "Henson", "Duraflex", "", ""], ["1999–2004", "Errea", "Towergate Insurance", "", ""], ["1996–1997", "UK", "Endsleigh Insurance", "", ""], ["2004–2008", "Errea", "Bence Building Merchants", "", ""], ["1985–1986", "Umbro", "Whitbread", "", ""], ["1997–1999", "Errea", "Endsleigh Insurance", "", ""], ["2011–2013", "Errea", "Mira Showers", "Barr Stadia", "Gloucestershire Echo"], ["1991–1993", "Technik", "Gulf Oil", "", ""], ["1988–1989", "", "Gulf Oil", "", ""], ["2009–2011", "Errea", "Mira Showers", "PSU Technology Group", ""], ["2013–", "Errea", "Mira Showers", "Gloucestershire College", "Gloucestershire Echo"], ["2008–", "Errea", "Mira Showers", "", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what time period had no shirt sponsor?
|
1982-1985
|
Answer:
| 128
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "400 m hurdles", "49.23"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "400 m hurdles", "48.45"], ["2001", "World Championships", "Edmonton, Canada", "18th (sf)", "400 m hurdles", "49.80"], ["2007", "World Championships", "Osaka, Japan", "3rd", "400 m hurdles", "48.12 (NR)"], ["1999", "European Junior Championships", "Riga, Latvia", "4th", "400 m hurdles", "52.17"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "400 m", "45.39 (CR, NR)"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "4x400 m relay", "3:05.50 (CR)"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "4x400 m relay", "3:03.32"], ["2001", "Universiade", "Beijing, China", "8th", "400 m hurdles", "49.68"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "7th (sf)", "400 m", "46.82"], ["2006", "European Championships", "Gothenburg, Sweden", "2nd", "400 m hurdles", "48.71"], ["2012", "European Championships", "Helsinki, Finland", "18th (sf)", "400 m hurdles", "50.77"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "3rd", "4x400 m relay", "3:06.61"], ["2007", "World Championships", "Osaka, Japan", "3rd", "4x400 m relay", "3:00.05"], ["2002", "European Championships", "Munich, Germany", "4th", "400 m", "45.40"], ["2008", "Olympic Games", "Beijing, China", "6th", "400 m hurdles", "48.42"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when was his first 1st place record?
|
2000
|
Answer:
| 128
|
Table InputTable: [["Season", "Team", "Record", "Head Coach", "Quarterback", "Leading Rusher", "Leading Receiver", "All-Pros", "Runner Up"], ["1972", "Washington Redskins", "11–3", "George Allen*", "Billy Kilmer", "Larry Brown", "Charley Taylor*", "Brown, Hanburger*", "Dallas Cowboys"], ["1971", "Dallas Cowboys†", "11–3", "Tom Landry*", "Roger Staubach*", "Duane Thomas", "Bob Hayes*", "Lilly*, Niland, Wright*", "San Francisco 49ers"], ["1992", "Dallas Cowboys†", "13–3", "Jimmy Johnson", "Troy Aikman*", "Emmitt Smith*", "Michael Irvin*", "Novacek, Smith*", "San Francisco 49ers"], ["1981", "San Francisco 49ers†", "13–3", "Bill Walsh*", "Joe Montana*", "Ricky Patton", "Dwight Clark", "Dean*, Lott*", "Dallas Cowboys"], ["1994", "San Francisco 49ers†", "13–3", "George Seifert", "Steve Young*", "Ricky Watters", "Jerry Rice*", "Rice*, Sanders*, Young*", "Dallas Cowboys"], ["1977", "Dallas Cowboys†", "12–2", "Tom Landry*", "Roger Staubach*", "Tony Dorsett*", "Drew Pearson", "Harris, Herrera, Martin, Pearson", "Minnesota Vikings"], ["1990", "New York Giants†", "13–3", "Bill Parcells*", "Phil Simms", "Ottis Anderson", "Stephen Baker", "Johnson, Landeta", "San Francisco 49ers"], ["1991", "Washington Redskins†", "14–2", "Joe Gibbs*", "Mark Rypien", "Earnest Byner", "Gary Clark", "Green*, Lachey", "Detroit Lions"], ["1996", "Green Bay Packers†", "13–3", "Mike Holmgren", "Brett Favre", "Edgar Bennett", "Antonio Freeman", "Butler, Favre", "Carolina Panthers"], ["1988", "San Francisco 49ers†", "10–6", "Bill Walsh*", "Joe Montana*", "Roger Craig", "Jerry Rice*", "Craig, Rice*", "Chicago Bears"], ["1999", "St. Louis Rams†", "13–3", "Dick Vermeil", "Kurt Warner", "Marshall Faulk*", "Isaac Bruce", "Carter, Faulk*, Pace, Warner", "Tampa Bay Buccaneers"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in which three consecutive years was the record the same?
|
2004, 2005, 2006
|
Answer:
| 128
|
Table InputTable: [["Name", "League", "FA Cup", "League Cup", "JP Trophy", "Total"], ["Pat Baldwin", "1", "0", "0", "0", "1"], ["Jamie Cureton", "20", "0", "0", "0", "20"], ["John O'Flynn", "11", "0", "1", "0", "12"], ["Danny Coles", "3", "0", "0", "0", "3"], ["Liam Sercombe", "1", "0", "0", "0", "1"], ["Scot Bennett", "5", "0", "0", "0", "5"], ["Jimmy Keohane", "3", "0", "0", "0", "3"], ["Alan Gow", "4", "0", "0", "0", "4"], ["Arron Davies", "3", "0", "0", "0", "3"], ["Jake Gosling", "1", "0", "0", "0", "1"], ["Total", "0", "0", "0", "0", "0"], ["Guillem Bauza", "2", "0", "0", "0", "2"], ["OWN GOALS", "0", "0", "0", "0", "0"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:does pat or john have the highest total?
|
John
|
Answer:
| 128
|
Table InputTable: [["Tournament", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014", "W–L"], ["Year End Ranking", "129", "91", "68", "90", "62", "41", "33", "39", "76", "62", "", ""], ["Win–Loss", "1–1", "2–4", "2–4", "2–4", "6–4", "3–4", "2–4", "6–4", "2–4", "0–4", "1–1", "27–38"], ["Win–Loss", "0–0", "0–1", "1–1", "4–4", "1–2", "2–6", "11–6", "5–8", "5–5", "0–2", "", "29–35"], ["Canada Masters", "A", "A", "A", "A", "A", "1R", "A", "A", "A", "A", "", "0–1"], ["Cincinnati Masters", "A", "A", "A", "LQ", "A", "3R", "A", "1R", "A", "A", "", "2–2"], ["Titles–Finals", "0–0", "0–0", "0–0", "0–0", "0–0", "1–1", "1–2", "0–0", "0–0", "0–2", "", "2–5"], ["Indian Wells Masters", "A", "A", "A", "3R", "2R", "1R", "4R", "2R", "3R", "A", "A", "8–6"], ["Madrid Masters", "A", "A", "A", "LQ", "LQ", "1R", "3R", "3R", "2R", "1R", "", "5–5"], ["Miami Masters", "A", "A", "A", "2R", "1R", "1R", "2R", "2R", "2R", "A", "", "3–6"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the combined score of year end rankings before 2009?
|
440
|
Answer:
| 128
|
Table InputTable: [["Ship", "Type of Vessel", "Lake", "Location", "Lives lost"], ["Charles S. Price", "Steamer", "Lake Huron", "near Port Huron, Michigan", "28 lost"], ["John A. McGean", "Steamer", "Lake Huron", "near Goderich, Ontario", "28 lost"], ["Issac M. Scott", "Steamer", "Lake Huron", "near Port Elgin, Ontario", "28 lost"], ["Hydrus", "Steamer", "Lake Huron", "near Lexington, Michigan", "28 lost"], ["Wexford", "Steamer", "Lake Huron", "north of Grand Bend, Ontario", "all hands"], ["Lightship No. 82", "Lightship", "Lake Erie", "Point Albino (near Buffalo)", "6 lost"], ["Argus", "Steamer", "Lake Huron", "25 miles off Kincardine, Ontario", "25 lost"], ["Regina", "Steamer", "Lake Huron", "near Harbor Beach, Michigan", ""], ["James Carruthers", "Steamer", "Lake Huron", "near Kincardine", "18 lost"], ["Plymouth", "Barge", "Lake Michigan", "", "7 lost"], ["Henry B. Smith", "Steamer", "Lake Superior", "", "all hands"], ["Leafield", "Steamer", "Lake Superior", "", "all hands"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many more ships were wrecked in lake huron than in erie?
|
7
|
Answer:
| 128
|
Table InputTable: [["name", "glyph", "C string", "Unicode", "Unicode name"], ["c", "c", "c", "U+0063", "LATIN SMALL LETTER C"], ["C", "C", "C", "U+0043", "LATIN CAPITAL LETTER C"], ["tab", "", "\\\\t", "U+0009", "CHARACTER TABULATION (HT)"], ["underscore", "_", "_", "U+005F", "LOW LINE"], ["comma", ",", ",", "U+002C", "COMMA"], ["h", "h", "h", "U+0068", "LATIN SMALL LETTER H"], ["backspace", "", "\\\\b", "U+0008", "BACKSPACE (BS)"], ["H", "H", "H", "U+0048", "LATIN CAPITAL LETTER H"], ["asterisk", "*", "*", "U+002A", "ASTERISK"], ["A", "A", "A", "U+0041", "LATIN CAPITAL LETTER A"], ["K", "K", "K", "U+004B", "LATIN CAPITAL LETTER K"], ["S", "S", "S", "U+0053", "LATIN CAPITAL LETTER S"], ["k", "k", "k", "U+006B", "LATIN SMALL LETTER K"], ["s", "s", "s", "U+0073", "LATIN SMALL LETTER S"], ["a", "a", "a", "U+0061", "LATIN SMALL LETTER A"], ["F", "F", "F", "U+0046", "LATIN CAPITAL LETTER F"], ["NUL", "", "\\\\0", "U+0000", "NULL (NUL)"], ["circumflex", "^", "^", "U+005E", "CIRCUMFLEX ACCENT"], ["f", "f", "f", "U+0066", "LATIN SMALL LETTER F"], ["P", "P", "P", "U+0050", "LATIN CAPITAL LETTER P"], ["L", "L", "L", "U+004C", "LATIN CAPITAL LETTER L"], ["exclamation-mark", "!", "!", "U+0021", "EXCLAMATION MARK"], ["Z", "Z", "Z", "U+005A", "LATIN CAPITAL LETTER Z"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the only character with a blank c string?
|
space
|
Answer:
| 128
|
Table InputTable: [["Date", "Opponent#", "Rank#", "Site", "TV", "Result", "Attendance"], ["December 3", "vs. #6 Florida", "#3", "Georgia Dome • Atlanta, GA (SEC Championship Game)", "ABC", "L 23–24", "74,751"], ["November 19", "#6 Auburn", "#4", "Legion Field • Birmingham, AL (Iron Bowl)", "ABC", "W 21–14", "83,091"], ["November 12", "at #20 Mississippi State", "#6", "Scott Field • Starkville, MS (Rivalry)", "ABC", "W 29–25", "41,358"], ["January 2, 1995", "vs. #13 Ohio State*", "#6", "Citrus Bowl • Orlando, FL (Florida Citrus Bowl)", "ABC", "W 24–17", "71,195"], ["October 22", "Ole Miss", "#8", "Bryant–Denny Stadium • Tuscaloosa, AL (Rivalry)", "ABC", "W 21–10", "70,123"], ["October 8", "Southern Miss*", "#11", "Bryant–Denny Stadium • Tuscaloosa, AL", "", "W 14–6", "70,123"], ["September 3", "Tennessee–Chattanooga*", "#11", "Legion Field • Birmingham, AL", "", "W 42–13", "82,109"], ["September 10", "Vanderbilt", "#11", "Bryant–Denny Stadium • Tuscaloosa, AL", "JPS", "W 17–7", "70,123"], ["September 24", "Tulane*", "#11", "Legion Field • Birmingham, AL", "", "W 20–10", "81,421"], ["September 17", "at Arkansas", "#12", "Razorback Stadium • Fayetteville, AR", "ABC", "W 13–6", "52,089"], ["October 1", "Georgia", "#11", "Bryant–Denny Stadium • Tuscaloosa, AL", "ESPN", "W 29–28", "70,123"], ["November 5", "at LSU", "#6", "Tiger Stadium • Baton Rouge, LA (Rivalry)", "ESPN", "W 35–17", "75,453"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of points scored by the tide in the last 3 games combined.
|
68
|
Answer:
| 128
|
Table InputTable: [["Pos", "Rider", "Manufacturer", "Time/Retired", "Points"], ["12", "Sebastian Porto", "Yamaha", "+27.054", "4"], ["2", "Valentino Rossi", "Aprilia", "+0.180", "20"], ["16", "Luca Boscoscuro", "TSR-Honda", "+56.432", ""], ["24", "Henk Van De Lagemaat", "Honda", "+1 Lap", ""], ["1", "Loris Capirossi", "Honda", "38:04.730", "25"], ["Ret", "Andre Romein", "Honda", "Retirement", ""], ["8", "Stefano Perugini", "Honda", "+20.891", "8"], ["7", "Franco Battaini", "Aprilia", "+20.889", "9"], ["20", "Lucas Oliver Bulto", "Yamaha", "+1:25.758", ""], ["22", "Rudie Markink", "Aprilia", "+1:40.280", ""], ["Ret", "Roberto Rolfo", "Aprilia", "Retirement", ""], ["15", "Jarno Janssen", "TSR-Honda", "+56.248", "1"], ["18", "Julien Allemand", "TSR-Honda", "+1:16.347", ""], ["23", "Arno Visscher", "Aprilia", "+1:40.635", ""], ["11", "Alex Hofmann", "TSR-Honda", "+26.933", "5"], ["Ret", "Maurice Bolwerk", "TSR-Honda", "Retirement", ""], ["21", "David Garcia", "Yamaha", "+1:33.867", ""], ["17", "Johann Stigefelt", "Yamaha", "+1:07.433", ""], ["3", "Jeremy McWilliams", "Aprilia", "+0.534", "16"], ["Ret", "Marcellino Lucchi", "Aprilia", "Retirement", ""], ["6", "Ralf Waldmann", "Aprilia", "+7.019", "10"], ["4", "Tohru Ukawa", "Honda", "+0.537", "13"], ["19", "Fonsi Nieto", "Yamaha", "+1:25.622", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who came immediately after sebastian porto in the race?
|
Tomomi Manako
|
Answer:
| 128
|
Table InputTable: [["Date", "Festival", "Location", "Awards", "Link"], ["Oct 9, Oct 11", "Sitges Film Festival", "Sitges, Catalonia\\n Spain", "", "Sitges Festival"], ["Oct 1, Oct 15", "Gwacheon International SF Festival", "Gwacheon, Gyeonggi-do\\n South Korea", "", "gisf.org"], ["Sep 28", "Fantastic Fest", "Austin, Texas\\n USA", "", "FantasticFest.com"], ["Nov 16–18", "AFF", "Wrocław, Lower Silesia\\n Poland", "", "AFF Poland"], ["Oct 9", "London Int. Festival of Science Fiction Film", "London, England\\n UK", "Closing Night Film", "Sci-Fi London"], ["Sep 19", "Lund International Fantastic Film Festival", "Lund, Skåne\\n Sweden", "", "fff.se"], ["Nov 12, Nov 18", "Indonesia Fantastic Film Festival", "Jakarta, Bandung\\n Indonesia", "", "inaff.com"], ["Oct 17, Oct 20", "Icon TLV", "Tel Aviv, Central\\n Israel", "", "icon.org.il"], ["Feb 2–5, Feb 11", "Santa Barbara International Film Festival", "Santa Barbara, California USA", "Top 11 \"Best of the Fest\" Selection", "sbiff.org"], ["Sep 16", "Athens International Film Festival", "Athens, Attica\\n Greece", "Best Director", "aiff.gr"], ["May 21–22, Jun 11", "Seattle International Film Festival", "Seattle, Washington USA", "", "siff.net"], ["Nov 11", "Les Utopiales", "Nantes, Pays de la Loire\\n France", "", "utopiales.org"], ["Jul 18, Jul 25", "Fantasia Festival", "Montreal, Quebec Canada", "Special Mention\\n\"for the resourcefulness and unwavering determination by a director to realize his unique vision\"", "FanTasia"], ["Oct 23", "Toronto After Dark", "Toronto, Ontario\\n Canada", "Best Special Effects\\nBest Musical Score", "torontoafterdark.com"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the total number of festivals that occurred in october?
|
5
|
Answer:
| 128
|
Table InputTable: [["Name", "City", "Hospital beds", "Operating rooms", "Total", "Trauma designation", "Affiliation", "Notes"], ["Vidant Edgecombe Hospital", "Tarboro", "117", "8", "125", "-", "Vidant", "-"], ["Alleghany Memorial Hospital", "Sparta", "41", "2", "43", "-", "QHR", "-"], ["Lenoir Memorial Hospital", "Kinston", "261", "12", "273", "-", "-", "-"], ["Harris Regional Hospital", "Sylva", "86", "7", "93", "-", "-", "-"], ["Hugh Chatham Memorial Hospital", "Elkin", "220", "8", "228", "-", "QHR", "-"], ["Morehead Memorial Hospital", "Eden", "229", "8", "237", "-", "QHR", "-"], ["Grace Hospital", "Morganton", "184", "7", "191", "-", "CHS", "-"], ["Annie Penn Hospital", "Reidsville", "110", "6", "116", "-", "Cone", "-"], ["Pender Memorial Hospital", "Burgaw", "86", "3", "89", "-", "NHRMC", "-"], ["Select Specialty Hospital - Durham", "Durham", "30", "0", "30", "-", "-", "-"], ["Martin General Hospital", "Williamston", "49", "3", "52", "-", "-", "-"], ["FirstHealth Richmond Memorial Hospital", "Rockingham", "150", "6", "156", "-", "FirstHealth", "-"], ["Hoots Memorial Hospital", "Yadkinville", "22", "3", "25", "-", "-", "-"], ["J. Arthur Dosher Memorial Hospital", "Southport", "100", "4", "104", "-", "-", "-"], ["Iredell Memorial Hospital", "Statesville", "247", "14", "261", "-", "-", "-"], ["Select Specialty Hospital - Winston-Salem", "Winston-Salem", "42", "0", "42", "-", "-", "-"], ["Vidant Chowan Hospital", "Edenton", "89", "4", "93", "-", "Vidant", "-"], ["Valdese General Hospital", "Valdese", "131", "6", "137", "-", "CHS", "-"], ["FirstHealth Moore Regional Hospital Hoke Campus", "Pinehurst, North Carolina", "8", "1", "9", "-", "FirstHealth", "-"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the only hospital to have 6 hospital beds?
|
Vidant Bertie Hospital
|
Answer:
| 128
|
Table InputTable: [["Model", "1991", "1995", "1996", "1997", "1998", "1999", "2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013"], ["Škoda Superb", "−", "−", "−", "−", "−", "−", "−", "177", "16,867", "23,135", "22,392", "22,091", "20,989", "20,530", "25,645", "44,548", "98,873", "116,700", "106,847", "94,400"], ["Škoda Fabia", "−", "−", "−", "−", "−", "823", "128,872", "250,978", "264,641", "260,988", "247,600", "236,698", "243,982", "232,890", "246,561", "264,173", "229,045", "266,800", "255,025", "202,000"], ["Škoda Felicia", "172,000", "210,000", "", "288,458", "261,127", "241,256", "148,028", "44,963", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−"], ["Škoda Octavia", "−", "−", "", "47,876", "102,373", "143,251", "158,503", "164,134", "164,017", "165,635", "181,683", "233,322", "270,274", "309,951", "344,857", "317,335", "349,746", "387,200", "409,360", "359,600"], ["Škoda Rapid", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "1,700", "9,292", "103,800"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of skoda cars sold in the year 2005?
|
492,111
|
Answer:
| 128
|
Table InputTable: [["Outcome", "No.", "Date", "Championship", "Surface", "Opponent in the final", "Score in the final"], ["Winner", "3.", "June 13, 1994", "London (Queen's Club), UK", "Grass", "Pete Sampras", "7–6(7–4), 7–6(7–4)"], ["Winner", "1.", "May 17, 1993", "Coral Springs, Florida, USA", "Clay", "David Wheaton", "6–3, 6–4"], ["Runner-up", "7.", "May 9, 1994", "Pinehurst, USA", "Clay", "Jared Palmer", "4–6, 6–7(5–7)"], ["Winner", "5.", "January 15, 1996", "Sydney, Australia", "Hard", "Goran Ivanišević", "5–7, 6–3, 6–4"], ["Winner", "7.", "November 16, 1998", "Stockholm, Sweden", "Hard", "Thomas Johansson", "6–3, 6–4, 6–4"], ["Runner-up", "6.", "May 2, 1994", "Atlanta, Georgia, USA", "Clay", "Michael Chang", "7–6(7–4), 6–7(4–7), 0–6"], ["Winner", "8.", "January 18, 1999", "Sydney, Australia", "Hard", "Àlex Corretja", "6–3, 7–6(7–5)"], ["Winner", "4.", "February 20, 1995", "Memphis, Tennessee, USA", "Hard", "Paul Haarhuis", "7–6(7–2), 6–4"], ["Runner-up", "10.", "August 22, 1996", "Stockholm, Sweden", "Hard (i)", "Thomas Enqvist", "5–7, 4–6, 6–7(0–7)"], ["Runner-up", "4.", "October 18, 1993", "Tokyo, Japan", "Carpet", "Ivan Lendl", "4–6, 4–6"], ["Winner", "6.", "April 20, 1998", "Barcelona, Spain", "Clay", "Alberto Berasategui", "6–2, 1–6, 6–3, 6–2"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the number of times won on grass?
|
1
|
Answer:
| 128
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "Argentina", "1", "2", "5", "8"], ["9", "Uruguay", "0", "0", "1", "1"], ["1", "Brazil", "7", "5", "3", "15"], ["4", "Chile", "2", "0", "2", "4"], ["2", "Venezuela", "3", "2", "8", "13"], ["Total", "Total", "16", "16", "30", "62"], ["3", "Colombia", "2", "3", "4", "9"], ["9", "Panama", "0", "0", "1", "1"], ["6", "Peru", "1", "1", "2", "4"], ["9", "Netherlands Antilles", "0", "0", "1", "1"], ["7", "Ecuador", "0", "2", "2", "4"], ["9", "Aruba", "0", "0", "1", "1"], ["8", "Guyana", "0", "1", "0", "1"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who won the most gold medals?
|
Brazil
|
Answer:
| 128
|
Table InputTable: [["Place", "Rider", "Country", "Team", "Points", "Wins"], ["1", "Sylvain Geboers", "Belgium", "Suzuki", "3066", "3"], ["8", "Gaston Rahier", "Belgium", "ČZ", "1112", "0"], ["5", "Joel Robert", "Belgium", "Suzuki", "1730", "1"], ["4", "Roger De Coster", "Belgium", "Suzuki", "1865", "3"], ["9", "Pierre Karsmakers", "Netherlands", "Husqvarna", "1110", "0"], ["16", "Gary Jones", "United States", "Yamaha", "439", "0"], ["7", "Willy Bauer", "Germany", "Maico", "1276", "0"], ["12", "Andy Roberton", "United Kingdom", "Husqvarna", "810", "0"], ["13", "Vlastimil Valek", "Czechoslovakia", "ČZ", "709", "0"], ["3", "Torlief Hansen", "Sweden", "Husqvarna", "2052", "0"], ["17", "John DeSoto", "United States", "Suzuki", "425", "0"], ["20", "Peter Lamppu", "United States", "Montesa", "309", "0"], ["10", "Dave Bickers", "United Kingdom", "ČZ", "1076", "0"], ["19", "Uno Palm", "Sweden", "Husqvarna", "324", "0"], ["14", "Mark Blackwell", "United States", "Husqvarna", "604", "0"], ["18", "Chris Horsefield", "United Kingdom", "ČZ", "416", "0"], ["2", "Adolf Weil", "Germany", "Maico", "2331", "2"], ["15", "Brad Lackey", "United States", "ČZ", "603", "0"], ["11", "John Banks", "United Kingdom", "ČZ", "971", "0"], ["6", "Heikki Mikkola", "Finland", "Husqvarna", "1680", "2"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:total wins by belgian riders
|
7
|
Answer:
| 128
|
Table InputTable: [["Position", "Sail Number", "Yacht", "State/Country", "Yacht Type", "LOA\\n(Metres)", "Skipper", "Elapsed Time\\nd:hh:mm:ss"], ["3", "YC1000", "Ausmaid", "SA", "Farr 47", "14.24", "Kevan Pearce", "3:06:02:29"], ["4", "AUS70", "Ragamuffin", "NSW", "Farr 50", "15.15", "Syd Fischer", "3:06:11:29"], ["9", "4826", "Aspect Computing", "NSW", "Radford 16.5 Sloop", "16.50", "David Pescud", "3:15:28:24"], ["7", "6606", "Quest", "NSW", "Nelson Marek 46", "14.12", "Bob Steel", "3:14:41:28"], ["2", "C1", "Brindabella", "NSW", "Jutson 79", "24.07", "George Snow", "2:21:55:06"], ["10", "8338", "AFR Midnight Rambler", "NSW", "Hick 35", "10.66", "Ed Psaltis\\nBob Thomas", "3:16:04:40"], ["8", "9090", "Industrial Quest", "QLD", "Nelson Marek 43", "13.11", "Kevin Miller", "3:14:58:46"], ["6", "SM1", "Fudge", "VIC", "Elliot 56", "17.07", "Peter Hansen", "3:11:00:26"], ["1", "US17", "Sayonara", "USA", "Farr ILC Maxi", "24.13", "Larry Ellison", "2:19:03:32"], ["5", "COK1", "Nokia", "CI", "Farr Ketch Maxi", "25.20", "David Witt", "3:09:19:00"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what yacht had the next best time (smaller time is better) than ausmaid?
|
Brindabella
|
Answer:
| 128
|
Table InputTable: [["Match", "Date", "Venue", "Opponents", "Score"], ["GL-B-5", "2008..", "[[]]", "[[]]", "-"], ["GL-B-1", "2008..", "[[]]", "[[]]", "-"], ["GL-B-2", "2008..", "[[]]", "[[]]", "-"], ["GL-B-4", "2008..", "[[]]", "[[]]", "-"], ["GL-B-3", "2008..", "[[]]", "[[]]", "-"], ["GL-B-6", "2008..", "[[]]", "[[]]", "-"], ["Quarterfinals-2", "2008..", "[[]]", "[[]]", "-"], ["Quarterfinals-1", "2008..", "[[]]", "[[]]", "-"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what match comes after gl-b-5?
|
GL-B-6
|
Answer:
| 128
|
Table InputTable: [["Series", "Premiere", "Finale", "Winner", "Runner-up", "Third place", "Host(s)", "Judging panel", "Guest judge(s)"], ["Eight", "12 April 2014", "31 May 2014", "TBA", "TBA", "TBA", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams", "Ant & Dec"], ["One", "9 June 2007", "17 June 2007", "Paul Potts", "Damon Scott", "Connie Talbot", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "N/A"], ["Five", "16 April 2011", "4 June 2011", "Jai McDowall", "Ronan Parke", "New Bounce", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nDavid Hasselhoff\\nMichael McIntyre", "Louis Walsh"], ["Three", "11 April 2009", "30 May 2009", "Diversity", "Susan Boyle", "Julian Smith", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "Kelly Brook"], ["Seven", "13 April 2013", "8 June 2013", "Attraction", "Jack Carroll", "Richard & Adam", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams", "N/A"], ["Six", "24 March 2012", "12 May 2012", "Ashleigh and Pudsey", "Jonathan and Charlotte", "Only Boys Aloud", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams", "Carmen Electra"], ["Two", "12 April 2008", "31 May 2008", "George Sampson", "Signature", "Andrew Johnston", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "N/A"], ["Nine", "2015", "2015", "TBA", "TBA", "TBA", "Ant & Dec", "TBA", "TBA"], ["Four", "17 April 2010", "5 June 2010", "Spelbound", "Twist and Pulse", "Kieran Gaffney", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "Louis Walsh"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was amanda on the judging panel?
|
3
|
Answer:
| 128
|
Table InputTable: [["Year", "Award", "Nominated work", "Category", "Result"], ["2008", "Glamour Woman Of The Year Awards", "Leona Lewis", "UK Solo Artist", "Won"], ["2008", "Britain's Best", "Leona Lewis", "Music Award", "Won"], ["2008", "Capital Awards", "Leona Lewis", "Favourite UK Female Artist", "Won"], ["2009", "BEFFTA Awards", "Leona Lewis", "Best Female Act", "Won"], ["2008", "Billboard 2008 Year End Award", "Leona Lewis", "Best New Artist", "Won"], ["2007", "Cosmopolitan Ultimate Woman of the Year", "Leona Lewis", "Newcomer of the Year", "Won"], ["2009", "Cosmopolitan Awards", "Leona Lewis", "Ultimate Music Star", "Won"], ["2008", "NewNowNext Awards", "Leona Lewis", "The Kylie Award: Next International Crossover", "Won"], ["2008", "PETA", "Leona Lewis", "Person Of The Year", "Won"], ["2008", "New Music Weekly Awards", "Leona Lewis", "Top 40 New Artist of the Year", "Won"], ["2009", "NAACP Image Awards", "Leona Lewis", "Outstanding New Artist", "Nominated"], ["2008", "Bambi Award", "Leona Lewis", "Shooting Star", "Won"], ["2009", "Swiss Music Awards", "Leona Lewis", "Best International Newcomer", "Won"], ["2009", "PETA - Sexiest Vegetarian Alive Awards", "Leona Lewis", "Sexiest Vegetarian Celebrity 2009", "Won"], ["2009", "Japan Gold Disc Awards", "Leona Lewis", "New Artist Of The Year", "Won"], ["2009", "APRA Awards", "\"Bleeding Love\"", "Most Played Foreign Work", "Won"], ["2008", "UK Music Video Awards", "\"Bleeding Love\"", "People's Choice Award", "Won"], ["2007", "The Record of the Year", "\"Bleeding Love\"", "The Record of the Year", "Won"], ["2008", "Vh1 Video of the Year", "\"Bleeding Love\"", "Best Video", "Won"], ["2009", "HITO Pop Music Awards", "\"Bleeding Love\"", "Best Western Song", "Won"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many awards has leona lewis won?
|
20
|
Answer:
| 128
|
Table InputTable: [["Season", "League\\nPos.", "League\\nCompetition", "League\\nTop scorer", "Danish Cup", "Europe", "Others"], ["2008-09", "3", "2008-09 Superliga", "Morten Rasmussen (9)\\nAlexander Farnerud (9)\\nOusman Jallow (9)", "Semi-final", "EC3 1st round", ""], ["2001-02", "1", "2001-02 Superliga", "Peter Madsen (22)", "5th round", "EC3 3rd round", ""], ["2004-05", "1", "2004-05 Superliga", "Thomas Kahlenberg (13)", "Winner", "EC3 qual 2nd round", "Royal League group stage"], ["1992-93", "3", "1992-93 Superliga", "Kim Vilfort (10)", "5th round", "", ""], ["2005-06", "2", "2005-06 Superliga", "Johan Elmander (13)", "Semi-final", "EC1 qual 3rd round\\nEC3 group stage", "Royal League group stage\\nDanish League Cup winner"], ["1993-94", "3", "1993-94 Superliga", "Mark Strudal (13)", "Winner", "EC3 3rd round", ""], ["1991-92", "7", "1991-92 Superliga", "Kim Vilfort (9)", "4th round", "EC1 2nd round", ""], ["1999-00", "2", "1999-00 Superliga", "Bent Christensen (13)", "Semi-final", "EC1 qual 3rd round\\nEC3 1st round", ""], ["2006-07", "6", "2006-07 Superliga", "Morten Rasmussen (15)", "4th round", "EC3 1st round", "Royal League winner\\nDanish League Cup winner"], ["2000-01", "2", "2000-01 Superliga", "Peter Graulund (21)", "Quarter-final", "EC1 qual 3rd round\\nEC3 1st round", ""], ["2009-10", "3", "2009-10 Superliga", "Morten Rasmussen (12)", "4th round", "EC3 qual play-off round", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the top scorer in the last season?
|
Simon Makienok Christoffersen
|
Answer:
| 128
|
Table InputTable: [["Contestant", "Original Tribe", "Switched Tribe", "Merged Tribe", "Finish", "Total Votes"], ["Aleksandr Lykov\\n41.the actor", "Barracudas", "Barracudas", "Crocodiles", "13th Voted Out\\n8th Jury Member\\nDay 37", "6"], ["Vera Glagoleva\\n46.the actress", "", "", "Crocodiles", "11th Voted Out\\n6th Jury Member\\nDay 33", "4"], ["Olga Orlova\\n25.the singer", "Barracudas", "Baracudas", "Crocodiles", "Eliminated\\n9th Jury Member\\nDay 38", "10"], ["Ivar Kalnynsh\\n54.the actor", "", "", "Crocodiles", "10th Voted Out\\n5th Jury Member\\nDay 30", "3"], ["Larisa Verbitskaya\\n43.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "12th Voted Out\\n7th Jury Member\\nDay 36", "11"], ["Marina Aleksandrova\\n20.the actress", "Barracudas", "Pelicans", "Crocodiles", "9th Voted Out\\n4th Jury Member\\nDay 27", "6"], ["Yelena Proklova\\n49.the TV presenter", "Pelicans", "Barracudas", "Crocodiles", "8th Voted Out\\n3rd Jury Member\\nDay 24", "4"], ["Viktor Gusev\\n47.the sport commentator", "Pelicans", "Pelicans", "Crocodiles", "7th Voted Out\\n1st Jury Member\\nDay 21", "6"], ["Ivan Demidov\\n39.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "Eliminated\\n2nd Jury Member\\nDay 23", "3"], ["Aleksandr Pashutin\\n60.the actor", "Barracudas", "", "", "3rd Voted Out\\nDay 9", "7"], ["Aleksandr Byalko\\n50.the physicist", "Pelicans", "Barracudas", "", "5th Voted Out\\nDay 15", "6"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many jury members were there?
|
9
|
Answer:
| 128
|
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2009", "13 Dec 2008", "Val d'Isère, France", "Giant slalom", "", "", "", ""], ["2010", "16 Jan 2010", "Wengen, Switzerland", "Downhill", "", "", "", ""], ["2009", "16 Jan 2009", "Wengen, Switzerland", "Super Combined", "", "", "", ""], ["2010", "10 Mar 2010", "Garmisch, Germany", "Downhill", "", "", "", ""], ["2008", "21", "64", "–", "28", "46", "46", "31"], ["2011", "5 Mar 2011", "Kranjska Gora, Slovenia", "Giant Slalom", "", "", "", ""], ["2010", "12 Mar 2010", "Garmisch, Germany", "Giant Slalom", "", "", "", ""], ["2014", "27", "18", "–", "25", "14", "20", "11"], ["2013", "26", "48", "–", "48", "27", "38", "4"], ["2009", "22", "7", "–", "6", "16", "16", "1"], ["2007", "20", "130", "–", "40", "–", "–", "—"], ["2010", "23", "1", "–", "2", "6", "2", "2"], ["2011", "24", "3", "–", "5", "6", "9", "6"], ["2012", "25", "24", "–", "16", "28", "17", "19"], ["2010", "6 Dec 2009", "Beaver Creek, USA", "Giant Slalom", "", "", "", ""], ["2010", "5 Dec 2009", "Beaver Creek, USA", "Downhill", "", "", "", ""], ["2010", "4 Dec 2009", "Beaver Creek, USA", "Super Combined", "", "", "", ""], ["Season", "Date", "Location", "Race", "", "", "", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was the val d'lsere, france location used?
|
1
|
Answer:
| 128
|
Table InputTable: [["Route", "Name", "Fare Type", "Terminals", "Terminals", "Major streets", "Notes", "History"], ["42, 43", "Mount Pleasant Line", "Local", "Mount Pleasant (Mount Pleasant & Lamont Streets NW)", "42 Gallery Place station\\n43 Farragut Square (AM End)\\n43 McPherson Square station (Franklin Square Entrance) (PM Start)", "42 Mount Pleasant Street NW, Columbia Road NW, Connecticut Avenue NW, H/I Streets NW\\n43 Mount Pleasant Street NW, Columbia Road NW, Connecticut Avenue NW", "42 serves Dupont Circle station\\n\\nsome peak hour trips terminate at Farragut Square\\n\\n\\n43: weekday peak hour service only\\n\\nTravels underneath Dupont Circle via the Connecticut Avenue underpass)", "See Mount Pleasant Line"], ["34", "Naylor Rd Line", "Local", "Archives (10th St & Pennsylvania Av NW)", "Naylor Road station", "Pennsylvania Avenue SE\\nIndependence Avenue SE/SW\\nNaylor Road SE", "", "34 operated to Friendship Heights station until replaced by the M5, which operated from Naylor Road station to Eastern Market station in 2007; 34 replaced the M5 in 2008 with the extension to the Archives station, also see Pennsylvania Avenue Line"], ["D8", "Hospital Center Line", "Local", "Washington Hospital Center", "Union Station", "Franklin Street NE\\nBrentwood Road NE\\nMount Olivet Rd NE\\nK Street NE", "Some trips end at Rhode Island Avenue – Brentwood station during the PM peak hour period", "D8 operated to Sibley Hospital (as part of the Glover Park-Trinidad Line) until replaced by the D6 (west of Union Station) in the mid-1990s"], ["D4", "Ivy City-Franklin Square Line", "Local", "Ivy City (New York Avenue & Fenwick Street NE)", "McPherson Square station (Franklin Square Entrance)", "K Street NW/NE", "", "D4 at first operated to Sibley Hospital (as part of the Glover Park-Trinidad Line) until replaced by D6 in the mid-1990s\\nIt then operated to Union Station (as the Ivy City-Union Station Line) until 2010, when it was extended to Franklin Square"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the name listed before mount pleasant line?
|
Pennsylvania Avenue Metro Extra Line
|
Answer:
| 128
|
Table InputTable: [["Team", "Stadium", "Capacity", "City/Area"], ["Bradford Bulls (2014 season)", "Provident Stadium", "27,000", "Bradford, West Yorkshire"], ["Salford City Reds (2014 season)", "Salford City Stadium", "12,000", "Salford, Greater Manchester"], ["Wigan Warriors (2014 season)", "DW Stadium", "25,138", "Wigan, Greater Manchester"], ["Huddersfield Giants (2014 season)", "John Smith's Stadium", "24,544", "Huddersfield, West Yorkshire"], ["Leeds Rhinos (2014 season)", "Headingley Carnegie Stadium", "22,250", "Leeds, West Yorkshire"], ["Castleford Tigers (2014 season)", "The Wish Communications Stadium", "11,750", "Castleford, West Yorkshire"], ["Hull (2014 season)", "Kingston Communications Stadium", "25,404", "Kingston upon Hull, East Riding of Yorkshire"], ["St Helens RLFC (2014 season)", "Langtree Park", "18,000", "St Helens, Merseyside"], ["Widnes Vikings (2014 season)", "The Select Security Stadium", "13,500", "Widnes, Cheshire, England"], ["Wakefield Trinity Wildcats (2014 season)", "Rapid Solicitors Stadium", "11,000", "Wakefield, West Yorkshire"], ["Warrington Wolves (2014 season)", "Halliwell Jones Stadium", "15,500", "Warrington, Cheshire"], ["London Broncos (2014 season)", "Twickenham Stoop", "12,700", "Twickenham, London"], ["Hull Kingston Rovers (2014 season)", "MS3 Craven Park", "9,471", "Kingston upon Hull, East Riding of Yorkshire"], ["Catalans Dragons (2014 season)", "Stade Gilbert Brutus", "14,000", "Perpignan, Pyrénées-Orientales, France"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the last stadium listed on this chart?
|
DW Stadium
|
Answer:
| 128
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["1987", "World Championships", "Rome, Italy", "13th", "Marathon", "2:17:45"], ["1990", "European Championships", "Split, FR Yugoslavia", "4th", "Marathon", "2:17:45"], ["1993", "World Championships", "Stuttgart, Germany", "—", "Marathon", "DNF"], ["1987", "Venice Marathon", "Venice, Italy", "1st", "Marathon", "2:10:01"], ["1992", "Olympic Games", "Barcelona, Spain", "5th", "Marathon", "2:14:15"], ["1986", "Venice Marathon", "Venice, Italy", "1st", "Marathon", "2:18:44"], ["1991", "World Championships", "Tokyo, Japan", "6th", "Marathon", "2:15:58"], ["1996", "Olympic Games", "Atlanta, United States", "20th", "Marathon", "2:17:27"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times did salvatore bettiol win first place across competitions?
|
2
|
Answer:
| 128
|
Table InputTable: [["School", "Season", "Record", "Conference Record", "Place", "Postseason"], ["Illinois", "1912–20", "85–34", "64–31", "–", ""], ["Illinois", "1915–16", "13–3", "9–3", "T2nd", ""], ["Illinois", "1917–18", "9–6", "6–6", "T4th", ""], ["Illinois", "1919–20", "9–4", "8–4", "3rd", ""], ["Illinois", "1912–13", "10–6", "7–6", "5th", ""], ["Illinois", "1913–14", "9–4", "7–3", "3rd", ""], ["Illinois", "1918–19", "6–8", "5–7", "5th", ""], ["Illinois", "1914–15", "16–0", "12–0", "T1st", "National Champions"], ["Illinois", "1916–17", "13–3", "10–2", "T1st", "Big Ten Champions"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which year did illinois not have any losses during the conference?
|
1914-15
|
Answer:
| 128
|
Table InputTable: [["Represent", "Candidate", "in Russian", "Age", "Height", "Hometown"], ["Capital City", "Natalia Varnakova", "Наталиа Варнакова", "19", "1.80 m (5 ft 11 in)", "Moscow"], ["Tambov Oblast", "Jenna Lerova", "Йенна Лерова", "21", "1.77 m (5 ft 9 1⁄2 in)", "Tambov"], ["Ryazan Oblast", "Julia Sandrova", "Юлиа Сандрова", "20", "1.74 m (5 ft 8 1⁄2 in)", "Ryazan"], ["Nenets Okrug", "Sofia Meldemendev", "Софиа Мелдемендев", "25", "1.85 m (6 ft 1 in)", "Naryan-Mar"], ["Saint Petersburg", "Maria Hernasova", "Мариа Хернасова", "20", "1.78 m (5 ft 10 in)", "Saint Petersburg"], ["Oryol Oblast", "Natalia Pavšukova", "Наталиа Павшукова", "19", "1.79 m (5 ft 10 1⁄2 in)", "Oryol"], ["Rostov Oblast", "Tatiana Kotova", "Татиана Котова", "21", "1.81 m (5 ft 11 1⁄2 in)", "Rostov-on-Don"], ["Sverdlovsk Oblast", "Julianna Piskunova", "Юлианна Пискунова", "22", "1.87 m (6 ft 1 1⁄2 in)", "Sverdlovsk"], ["Sakhalin Oblast", "Jeannette Menova", "Йеаннетте Менова", "18", "1.75 m (5 ft 9 in)", "Sakhalin"], ["Samara Oblast", "Nadia Gurina", "Надиа Гурина", "20", "1.78 m (5 ft 10 in)", "Samara"], ["Krasnodar Krai", "Patricia Valiahmetova", "Патрициа Валиахметова", "20", "1.80 m (5 ft 11 in)", "Krasnodar"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:natalia varnakova is the same height as which other contestant(s)?
|
Jahaira Novgorodova, Carmen Jenockova, Mariesea Mnesiču, Patricia Valiahmetova, Anastasija Larkova
|
Answer:
| 128
|
Table InputTable: [["District", "Incumbent", "2008 Status", "Democratic", "Republican"], ["7", "Ed Perlmutter", "Re-election", "Ed Perlmutter", "John W. Lerew"], ["3", "John Salazar", "Re-election", "John Salazar", "Wayne Wolf"], ["4", "Marilyn Musgrave", "Re-election", "Betsy Markey", "Marilyn Musgrave"], ["5", "Doug Lamborn", "Re-election", "Hal Bidlack", "Doug Lamborn"], ["1", "Diana DeGette", "Re-election", "Diana DeGette", "George Lilly"], ["2", "Mark Udall", "Open", "Jared Polis", "Scott Starin"], ["6", "Tom Tancredo", "Open", "Hank Eng", "Mike Coffman"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many candidates belong to a party other than republican or democrat?
|
0
|
Answer:
| 128
|
Table InputTable: [["Date", "Competition", "Location", "Country", "Event", "Placing", "Rider", "Nationality"], ["1 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "500 m time trial", "1", "Victoria Pendleton", "GBR"], ["2 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Ross Edgar", "GBR"], ["31 October 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Victoria Pendleton", "GBR"], ["2 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jason Kenny", "GBR"], ["30 October 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "500 m time trial", "2", "Victoria Pendleton", "GBR"], ["2 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Keirin", "1", "Victoria Pendleton", "GBR"], ["2 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jamie Staff", "GBR"], ["1 November 2008", "2008–09 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Jason Kenny", "GBR"], ["30 October 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Victoria Pendleton", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Ross Edgar", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Chris Hoy", "GBR"], ["30 October 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Chris Hoy", "GBR"], ["1 November 2009", "2009–10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jamie Staff", "GBR"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many competitions were not in the united kingdom?
|
4
|
Answer:
| 128
|
Table InputTable: [["Rank", "City", "Passengers", "Top Carriers"], ["5", "Dallas/Fort Worth, TX", "488,000", "American, United"], ["8", "Charlotte, NC", "441,000", "United, US Airways"], ["10", "Phoenix, AZ", "393,000", "United, US Airways"], ["9", "Atlanta, GA", "400,000", "Delta, United"], ["2", "Chicago, IL", "673,000", "American, Spirit, United"], ["4", "San Francisco, CA", "492,000", "United"], ["1", "Los Angeles, CA", "700,000", "American, Spirit, United"], ["3", "Denver, CO", "654,000", "Frontier, Spirit, United"], ["6", "Newark, NJ", "480,000", "United"], ["7", "Las Vegas, NV", "442,000", "Spirit, United"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many domestic routes out of houston intercontinental have united as a carrier?
|
10
|
Answer:
| 128
|
Table InputTable: [["Place", "Rider", "Country", "Team", "Points", "Wins"], ["2", "Adolf Weil", "Germany", "Maico", "2331", "2"], ["7", "Willy Bauer", "Germany", "Maico", "1276", "0"], ["1", "Sylvain Geboers", "Belgium", "Suzuki", "3066", "3"], ["8", "Gaston Rahier", "Belgium", "ČZ", "1112", "0"], ["13", "Vlastimil Valek", "Czechoslovakia", "ČZ", "709", "0"], ["3", "Torlief Hansen", "Sweden", "Husqvarna", "2052", "0"], ["9", "Pierre Karsmakers", "Netherlands", "Husqvarna", "1110", "0"], ["10", "Dave Bickers", "United Kingdom", "ČZ", "1076", "0"], ["4", "Roger De Coster", "Belgium", "Suzuki", "1865", "3"], ["17", "John DeSoto", "United States", "Suzuki", "425", "0"], ["5", "Joel Robert", "Belgium", "Suzuki", "1730", "1"], ["11", "John Banks", "United Kingdom", "ČZ", "971", "0"], ["12", "Andy Roberton", "United Kingdom", "Husqvarna", "810", "0"], ["20", "Peter Lamppu", "United States", "Montesa", "309", "0"], ["14", "Mark Blackwell", "United States", "Husqvarna", "604", "0"], ["15", "Brad Lackey", "United States", "ČZ", "603", "0"], ["16", "Gary Jones", "United States", "Yamaha", "439", "0"], ["18", "Chris Horsefield", "United Kingdom", "ČZ", "416", "0"], ["19", "Uno Palm", "Sweden", "Husqvarna", "324", "0"], ["6", "Heikki Mikkola", "Finland", "Husqvarna", "1680", "2"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in total, how many germans are listed?
|
2
|
Answer:
| 128
|
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2011", "24", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete"], ["2006", "19", "22", "–", "18", "37", "15", "—"], ["2005", "18", "37", "–", "27", "18", "49", "—"], ["2007", "20", "33", "–", "50", "15", "23", "—"], ["2004", "17", "112", "–", "–", "51", "–", "—"], ["2008", "21", "38", "–", "–", "35", "13", "—"], ["2013", "26", "37", "–", "17", "28", "30", "—"], ["2012", "25", "75", "–", "28", "–", "–", "—"], ["2009", "22", "9", "–", "40", "2", "5", "50"], ["2010", "23", "28", "–", "–", "13", "23", "—"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in what year are there the first results for giant slalom?
|
2005
|
Answer:
| 128
|
Table InputTable: [["Contestant", "Age", "Height", "Home City", "Rank"], ["Isabelle Raisa", "16", "170 cm (5 ft 7 in)", "Vienna", "Eliminated in Episode 1"], ["Michaela Schopf", "21", "172 cm (5 ft 7.5 in)", "Salzburg (originally from Germany)", "Quit in Episode 4"], ["Nadine Trinker", "21", "183 cm (6 ft 0 in)", "Bodensdorf", "Eliminated in Episode 9"], ["Dzejlana \"Lana\" Baltić", "20", "179 cm (5 ft 10.5 in)", "Graz (originally from Bosnia)", "1st Eliminated in Episode 10"], ["Christine Riener", "20", "181 cm (5 ft 11.25 in)", "Bludenz", "Eliminated in Episode 4"], ["Izabela Pop Kostić", "20", "170 cm (5 ft 7 in)", "Vienna (originally from Bosnia)", "Eliminated in Episode 8"], ["Katharina Mihalović", "23", "179 cm (5 ft 10.5 in)", "Vienna", "Eliminated in Episode 2"], ["Melisa Popanicić", "16", "175 cm (5 ft 9 in)", "Wörgl", "2nd Eliminated in Episode 10"], ["Sabrina Angelika Rauch †", "21", "175 cm (5 ft 9 in)", "Graz", "Eliminated in Episode 2"], ["Yemisi Rieger", "17", "177 cm (5 ft 9.5 in)", "Vienna", "Eliminated in Episode 7"], ["Gina Zeneb Adamu", "17", "175 cm (5 ft 9 in)", "Bad Vöslau", "Runner-Up"], ["Alina Chlebecek", "18", "170 cm (5 ft 7 in)", "Deutsch-Wagram", "Eliminated in Episode 1"], ["Nataša Marić", "16", "175 cm (5 ft 9 in)", "Liefering (originally from Serbia)", "Eliminated in Episode 3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in cycle 4 of austria's next top model,how many contestants were older than 20?
|
5
|
Answer:
| 128
|
Table InputTable: [["#", "Player", "Goals", "Caps", "Career"], ["2", "Clint Dempsey", "36", "103", "2004–present"], ["3", "Eric Wynalda", "34", "106", "1990–2000"], ["1", "Landon Donovan", "57", "155", "2000–present"], ["8", "Eddie Johnson", "19", "62", "2004–present"], ["4", "Brian McBride", "30", "95", "1993–2006"], ["5", "Joe-Max Moore", "24", "100", "1992–2002"], ["6T", "Bruce Murray", "21", "86", "1985–1993"], ["9T", "DaMarcus Beasley", "17", "114", "2001–present"], ["9T", "Earnie Stewart", "17", "101", "1990–2004"], ["6T", "Jozy Altidore", "21", "67", "2007–present"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who scored more goals: clint dempsey or eric wynalda?
|
Clint Dempsey
|
Answer:
| 128
|
Table InputTable: [["Name", "Country", "Town", "Height\\nmetres / ft", "Structural type", "Held record", "Notes"], ["St. Mary's Church", "Germany", "Stralsund", "151 / 500", "Church", "1549–1647", "Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341 ft)."], ["Eiffel Tower", "France", "Paris", "300.6 / 986", "Tower", "1889–1930", "Currently stands at a height of 324 metres (1,063 ft)."], ["Lincoln Cathedral", "England", "Lincoln", "159.7 / 524", "Church", "1311–1549", "Spire collapsed in 1549; today, stands at a height of 83 metres (272 ft)."], ["Cologne Cathedral", "Germany", "Cologne", "157.4 / 516", "Church", "1880–1884", ""], ["St Nikolai", "Germany", "Hamburg", "147.3 / 483", "Church", "1874–1876", "Due to aerial bombing in World War II the nave was demolished; only the spire remains."], ["Strasbourg Cathedral", "Germany and/or France (today France)", "Strasbourg", "142 / 470", "Church", "1647–1874", ""], ["Great Pyramid of Giza", "Egypt", "Giza", "146 / 480", "Mausoleum", "2570 BC–1311", "Due to erosion today it stands at the height of 138.8 metres (455 ft)."], ["Ostankino Tower", "Russia", "Moscow", "540 / 1,772", "Tower", "1967–1976", ""], ["Empire State Building", "United States", "New York City", "448 / 1,472", "Skyscraper", "1931–1967", ""], ["Chrysler Building", "United States", "New York City", "319 / 1,046", "Skyscraper", "1930–1931", ""], ["Burj Khalifa", "United Arab Emirates", "Dubai", "829.8 / 2,722", "Skyscraper", "2007–present", "Topped-out on 17 January 2009"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what building had the least height in germany?
|
St. Mary's Church
|
Answer:
| 128
|
Table InputTable: [["State\\n(linked to\\nsummaries below)", "Incumbent\\nSenator", "Incumbent\\nParty", "Incumbent\\nElectoral\\nhistory", "Most recent election results", "2018 intent", "Candidates"], ["Maine", "Angus King", "Independent", "Angus King (I) 52.9%\\nCharles E. Summers, Jr. (R) 30.7%\\nCynthia Dill (D) 13.3%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["New York", "Kirsten Gillibrand", "Democratic", "Kirsten Gillibrand (D) 71.6%\\nWendy E. Long (R) 26.0%", "2010 (special)\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Texas", "Ted Cruz", "Republican", "Ted Cruz (R) 56.5%\\nPaul Sadler (D) 40.7%\\nJohn Jay Myers (L) 2.1%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Missouri", "Claire McCaskill", "Democratic", "Claire McCaskill (D) 54.8%\\nTodd Akin (R) 39.0%\\nJonathan Dine (L) 6.1%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Vermont", "Bernie Sanders", "Independent", "Bernie Sanders (I) 71%\\nJohn MacGovern (R) 24.9%\\nCris Ericson (Marijuana Party) 2%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Rhode Island", "Sheldon Whitehouse", "Democratic", "Sheldon Whitehouse (D) 64.8%\\nBarry Hinckley (R) 35.0%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides republican (r) and democrat (d), what other party was represented in the maine election?
|
Independent
|
Answer:
| 128
|
Table InputTable: [["Season", "Conference", "Head Coach", "Total Wins", "Total Losses", "Total Ties", "Conference Wins", "Conference Losses", "Conference Ties", "Conference Standing", "Postseason Result"], ["Totals:\\n105 Seasons", "2 Conferences", "23 Head Coaches", "Total\\nWins\\n473", "Total\\nLosses\\n536", "Total\\nTies\\n32", "239 Conference Wins\\n55 SIAA\\n184 SoCon", "379 Conference Losses\\n58 SIAA\\n321 SoCon", "13 Conference Ties\\n8 SIAA\\n5 SoCon", "Regular Season\\nChampions\\n2 times", "1–0 Bowl Record\\n1–3 Playoff Record"], ["1992", "Southern", "Charlie Taaffe", "11", "2", "0", "6", "1", "0", "1", "Quarterfinals"], ["1988", "Southern", "Charlie Taaffe", "8", "4", "0", "5", "2", "0", "3", "First Round"], ["1990", "Southern", "Charlie Taaffe", "7", "5", "0", "4", "3", "0", "3", "First Round"], ["1958", "Southern", "Eddie Teague", "4", "6", "0", "2", "3", "0", "7", "—"], ["1944", "No Team", "No Team", "No Team", "No Team", "No Team", "No Team", "No Team", "No Team", "No Team", "No Team"], ["1963", "Southern", "Eddie Teague", "4", "6", "0", "2", "4", "0", "7", "—"], ["1957", "Southern", "Eddie Teague", "5", "4", "1", "4", "2", "0", "3", "—"], ["1959", "Southern", "Eddie Teague", "8", "2", "0", "5", "1", "0", "2", "—"], ["1918", "Southern Intercollegiate", "Harvey O'Brien", "0", "2", "1", "0", "1", "1", "—", "—"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which year did the team have their most total wins?
|
1992
|
Answer:
| 128
|
Table InputTable: [["Description Losses", "1939/40", "1940/41", "1941/42", "1942/43", "1943/44", "1944/45", "Total"], ["Deaths other countries", "", "", "", "", "", "", "2,000"], ["Deaths In Prisons & Camps", "69,000", "210,000", "220,000", "266,000", "381,000", "", "1,146,000"], ["Deaths Outside of Prisons & Camps", "", "42,000", "71,000", "142,000", "218,000", "", "473,000"], ["Direct War Losses", "360,000", "", "", "", "", "183,000", "543,000"], ["Total", "504,000", "352,000", "407,000", "541,000", "681,000", "270,000", "2,770,000"], ["Murdered in Eastern Regions", "", "", "", "", "", "100,000", "100,000"], ["Murdered", "75,000", "100,000", "116,000", "133,000", "82,000", "", "506,000"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the total of deaths that happened in 1939/1940?
|
504,000
|
Answer:
| 128
|
Table InputTable: [["Year", "Manufacturer", "Model", "Length (feet)", "Quantity", "Fleet Series", "Fuel Propulsion", "Powertrain"], ["2013", "Gillig", "Low-floor Advantage", "40", "65", "1301-1365", "Diesel", "Cummins ISL 280 HP \\nAllison B400 6-speed"], ["2013", "Gillig", "Low-floor Advantage", "40", "55", "6101-6155", "Diesel", "Cummins ISL 280 HP\\nAllison B400 6-speed"], ["2003", "Van Hool", "AG300", "60", "57", "2001-2057", "Diesel", "Cummins ISM\\nVoith D864.3E"], ["2013", "New Flyer", "Xcelsior D60", "60", "23", "2201-2223", "Diesel", "Cummins ISL 330 HP\\nAllison B400 6-speed"], ["2000", "MCI", "D4500", "45", "30", "6001-6030", "Diesel", ""], ["2007", "Van Hool", "AG300", "60", "10", "2101-2110", "Diesel", "Cummins ISL\\nVoith D864.3E"], ["2008", "Van Hool", "A300L", "40", "27", "1201-1227", "Diesel", "Cummins ISL\\nVoith D864.5"], ["1996", "New Flyer", "D60", "60 (articulated)", "30", "1901-1930*", "Diesel", "Detroit Diesel Series 50\\nAllison B400R"], ["2007", "Van Hool", "AG300", "60", "15", "2151-2165", "Diesel", "Cummins ISM\\nVoith D864.3E"], ["2003", "Van Hool", "A330", "40", "110", "1001-1110", "Diesel", "Cummins ISM\\nVoith D864.3E"], ["2001", "MCI", "D4500", "45", "10", "6031-6040", "Diesel", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of models covered in the table?
|
20
|
Answer:
| 128
|
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["5", "July 8", "Watkins Glen‡", "Hal Shaw, Jr.\\n Monte Shelton", "Porsche 935", "Brian Fuerstenau\\n Bob Tullius", "Jaguar XJS"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["3", "June 11", "Portland", "Tuck Thomas", "Chevrolet Monza", "Bob Matkowitch", "Chevrolet Corvette"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of wins by jaguar xjs?
|
7
|
Answer:
| 128
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["6", "Peru", "1", "1", "2", "4"], ["5", "Argentina", "1", "2", "5", "8"], ["2", "Venezuela", "3", "2", "8", "13"], ["7", "Ecuador", "0", "2", "2", "4"], ["1", "Brazil", "7", "5", "3", "15"], ["9", "Uruguay", "0", "0", "1", "1"], ["4", "Chile", "2", "0", "2", "4"], ["9", "Netherlands Antilles", "0", "0", "1", "1"], ["3", "Colombia", "2", "3", "4", "9"], ["9", "Panama", "0", "0", "1", "1"], ["8", "Guyana", "0", "1", "0", "1"], ["9", "Aruba", "0", "0", "1", "1"], ["Total", "Total", "16", "16", "30", "62"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:other nations besides peru to earn 2 bronze medals
|
Chile, Ecuador
|
Answer:
| 128
|
Table InputTable: [["Date", "Opponents", "Venue", "Result", "Scorers", "Attendance"], ["9 Sep 1920", "Bristol Rovers", "H", "0–2", "", "8,000"], ["16 Oct 1920", "Millwall", "A", "0–1", "", "20,000"], ["1 Sep 1920", "Bristol Rovers", "A", "2–3", "Walker, Wolstenholme", "10,000"], ["5 Mar 1921", "Brighton & Hove Albion", "A", "0–1", "", "8,000"], ["18 Sep 1920", "Plymouth Argyle", "H", "0–0", "", "8,000"], ["4 Dec 1920", "Watford", "H", "0–2", "", "6,000"], ["26 Feb 1921", "Brighton & Hove Albion", "H", "0–4", "", "8,000"], ["2 Oct 1920", "Exeter City", "H", "2–0", "Wolstenholme 2", "8,000"], ["27 Dec 1920", "Southend United", "A", "1–2", "Walker", "10,000"], ["30 Apr 1921", "Luton Town", "H", "2–0", "Devlin 2", "5,000"], ["27 Nov 1920", "Swindon Town", "A", "0–5", "", "7,000"], ["13 Jan 1921", "Norwich City", "H", "2–0", "Wright, Cox", "4,000"], ["9 Oct 1920", "Millwall", "H", "3–1", "Devlin 2, Walker", "14,000"], ["9 Apr 1921", "Swansea Town", "H", "1–1", "Walker", "6,000"], ["2 May 1921", "Southampton", "A", "0–0", "", "6,000"], ["22 Jan 1921", "Norwich City", "A", "0–3", "", "5,000"], ["6 Nov 1920", "Gillingham", "H", "1–0", "Wolstenholme", "7,000"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times were consecutive games played against millwall?
|
1
|
Answer:
| 128
|
Table InputTable: [["Season", "Series", "Team", "Races", "Wins", "Poles", "F/Laps", "Podiums", "Points", "Position"], ["2012", "Formula 3 Euro Series", "Angola Racing Team", "21", "0", "0", "0", "0", "14", "14th"], ["2012", "59th Macau Grand Prix Formula 3", "Angola Racing Team", "2", "0", "0", "0", "0", "—", "23rd"], ["2012", "Masters of Formula 3", "Angola Racing Team", "1", "0", "0", "0", "0", "—", "18th"], ["2012", "British Formula 3 Championship", "Angola Racing Team", "5", "0", "0", "0", "0", "—", "—"], ["2008", "Asian Formula Renault Challenge", "Champ Motorsports", "13", "0", "0", "0", "3", "193", "4th"], ["2011", "Formula Pilota China", "Asia Racing Team", "12", "2", "0", "0", "3", "124", "2nd"], ["2009", "Asian Formula Renault Challenge", "Asia Racing Team", "12", "6", "2", "4", "7", "287", "2nd"], ["2007", "Asian Formula Renault Challenge", "Champ Motorsports", "12", "0", "0", "0", "1", "64", "14th"], ["2010", "Austria Formula 3 Cup", "Sonangol Motopark", "4", "1", "2", "3", "2", "35", "9th"], ["2009", "Formula Renault 2.0 Northern European Cup", "Krenek Motorsport", "14", "0", "0", "0", "0", "44", "21st"], ["2013", "GP3 Series", "Carlin", "16", "0", "0", "0", "0", "0", "23rd"], ["2010", "ATS Formel 3 Cup", "China Sonangol", "5", "0", "0", "0", "0", "0", "19th"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides angola racing team, what other team is listed in the 23rd position?
|
Carlin
|
Answer:
| 128
|
Table InputTable: [["Rank", "Country", "Box Office", "Year", "Box office\\nfrom national films"], ["8", "Germany", "$1.3 billion", "2012", "–"], ["7", "India", "$1.4 billion", "2012", "–"], ["9", "Russia", "$1.2 billion", "2012", "–"], ["4", "United Kingdom", "$1.7 billion", "2012", "36.1% (2011)"], ["5", "France", "$1.7 billion", "2012", "33.3% (2013)"], ["6", "South Korea", "$1.47 billion", "2013", "59.7% (2013)"], ["-", "World", "$34.7 billion", "2012", "–"], ["12", "Brazil", "$0.72 billion", "2013", "17% (2013)"], ["1", "Canada/United States", "$10.8 billion", "2012", "–"], ["3", "Japan", "$1.88 billion", "2013", "61% (2013)"], ["10", "Australia", "$1.2 billion", "2012", "4.1% (2011)"], ["11", "Italy", "$0.84 billion", "2013", "30% (2013)"], ["2", "China", "$3.6 billion", "2013", "59% (2013)"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many countries had at least $1 billion in box office?
|
10
|
Answer:
| 128
|
Table InputTable: [["Frequency", "Call sign", "Name", "Format", "Owner", "Target city/market", "City of license"], ["104.1 FM", "WNAX-FM", "The Wolf 104.1", "Country", "Saga Communications", "Yankton/Vermillion", "Yankton"], ["106.3 FM", "KVHT", "Classic Hits 106.3", "Classic Hits", "Cullhane Communications, Inc.", "Yankton/Vermillion", "Vermillion"], ["93.1 FM", "KKYA", "KK93", "Country", "Riverfront Broadcasting LLC", "Yankton/Vermillion", "Yankton"], ["94.3 FM", "KDAM", "The Dam", "Mainstream Rock", "Riverfront Broadcasting LLC", "Yankton/Vermillion", "Hartington"], ["89.7 FM", "KUSD", "South Dakota Public Broadcasting", "NPR", "SD Board of Directors for Educational Telecommunications", "Yankton/Vermillion", "Vermillion"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what city has a radio station called the wolf?
|
Yankton
|
Answer:
| 128
|
Table InputTable: [["Film", "Film", "Date"], ["Kodachrome 25 film", "Movie film, 16 mm, daylight", "1974–2002"], ["Kodachrome film", "16 mm, daylight (ASA 10) & Type A (ASA 16)", "1935–1962"], ["Kodachrome Professional film", "35 mm, Type A (ASA 16)", "1956–1962"], ["Kodak Color Print Material", "Type D (slide duping film)", "1955–1957"], ["Kodachrome 40 film", "Movie film, 16 mm, Type A", "1974–2006"], ["Kodachrome II film", "16 mm, daylight (ASA 25) and Type A (ASA 40)", "1961–1974"], ["Kodachrome 25 film", "Professional film, 35 mm, daylight", "1983–1999"], ["Kodachrome 25 film", "Movie film, 8 mm, daylight", "1974–1992"], ["Kodachrome 64", "Professional film, 35 mm, daylight", "1983–2009"], ["Kodachrome film", "8 mm, daylight (ASA 10) & Type A (ASA 16)", "1936–1962"], ["Kodachrome 40 film", "Movie film, 8 mm, Type A", "1974–1992"], ["Kodachrome 200", "Professional film, 35 mm, daylight", "1986–2004"], ["Kodachrome II film", "Professional, 35 mm, Type A (ASA 40)", "1962–1978"], ["Kodachrome Professional film (sheets)", "daylight (ASA 8) and Type B (ASA 10)", "1938–1951"], ["Kodachrome film", "35 mm and 828, Type F (ASA 12)", "1955–1962"], ["Kodachrome II film", "35 mm and 828, daylight (ASA 25/early) (ASA 64/late)", "1961–1974"], ["Kodachrome 25 film", "35 mm, daylight", "1974–2001"], ["Kodachrome II film", "8 mm, daylight (ASA 25) and Type A (ASA 40)", "1961–1974"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the earliest date kodak made 16mm film?
|
1935
|
Answer:
| 128
|
Table InputTable: [["Rd.", "Event", "Circuit", "Location", "Date", "Winner"], ["6", "Supercheap Auto Bathurst 1000", "Mount Panorama Circuit", "Bathurst, New South Wales", "8-11 Oct", "Jonathon Webb"], ["3", "Dunlop Townsville 400", "Townsville Street Circuit", "Townsville, Queensland", "10-12 Jul", "James Moffat"], ["2", "Winton", "Winton Motor Raceway", "Benalla, Victoria", "1-3 May", "Jonathon Webb"], ["1", "Clipsal 500", "Adelaide Street Circuit", "Adelaide, South Australia", "19-22 Mar", "David Russell"], ["4", "Norton 360 Sandown Challenge", "Sandown Raceway", "Melbourne, Victoria", "31 Jul-Aug 2", "David Russell"], ["5", "Queensland House & Land 300", "Queensland Raceway", "Ipswich, Queensland", "21-23 Aug", "Jonathon Webb"], ["7", "Sydney Telstra 500", "Homebush Street Circuit", "Sydney, New South Wales", "4-6 Dec", "Jonathon Webb"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first to win during the 2009 fujitsu v8 supercar season?
|
David Russell
|
Answer:
| 128
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Notes"], ["2009", "World Championships", "Berlin, Germany", "22nd (q)", "5.40 m"], ["2011", "World Championships", "Daegu, South Korea", "9th", "5.65 m"], ["2012", "European Championships", "Helsinki, Finland", "6th", "5.60 m"], ["2014", "World Indoor Championships", "Sopot, Poland", "3rd", "5.80 m"], ["2006", "World Junior Championships", "Beijing, China", "5th", "5.30 m"], ["2010", "European Championships", "Barcelona, Spain", "10th", "5.60 m"], ["2013", "European Indoor Championships", "Gothenburg, Sweden", "5th", "5.71 m"], ["2005", "World Youth Championships", "Marrakech, Morocco", "6th", "5.05 m"], ["2008", "Olympic Games", "Beijing, China", "10th", "5.45 m"], ["2012", "Olympic Games", "London, United Kingdom", "8th", "5.65 m"], ["2009", "European U23 Championships", "Kaunas, Lithuania", "8th", "5.15 m"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which competition was held in berlin and daegu?
|
World Championships
|
Answer:
| 128
|
Table InputTable: [["Model", "1991", "1995", "1996", "1997", "1998", "1999", "2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013"], ["Škoda Superb", "−", "−", "−", "−", "−", "−", "−", "177", "16,867", "23,135", "22,392", "22,091", "20,989", "20,530", "25,645", "44,548", "98,873", "116,700", "106,847", "94,400"], ["Total", "172,000", "210,000", "261,000", "336,334", "363,500", "385,330", "435,403", "460,252", "445,525", "449,758", "451,675", "492,111", "549,667", "630,032", "674,530", "684,226", "762,600", "879,200", "949,412", "920,800"], ["Škoda Felicia", "172,000", "210,000", "", "288,458", "261,127", "241,256", "148,028", "44,963", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−", "−"], ["Škoda Octavia", "−", "−", "", "47,876", "102,373", "143,251", "158,503", "164,134", "164,017", "165,635", "181,683", "233,322", "270,274", "309,951", "344,857", "317,335", "349,746", "387,200", "409,360", "359,600"], ["Škoda Fabia", "−", "−", "−", "−", "−", "823", "128,872", "250,978", "264,641", "260,988", "247,600", "236,698", "243,982", "232,890", "246,561", "264,173", "229,045", "266,800", "255,025", "202,000"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:total number of cars sold in 2001?
|
460,252
|
Answer:
| 128
|
Table InputTable: [["Date", "Location", "Air/Ground", "Number", "Type", "Status"], ["27 November 1944", "South of Magdeburg, Germany", "Air", "4", "FW-190", "Destroyed"], ["25 January 1952", "Korea", "Air", "1", "Mig-15", "Damaged"], ["27 May 1944", "North of Strasbourg, France", "Air", "1", "Me-109", "Damaged"], ["13 April 1944", "West of Mannheim, Germany", "Air", "1", "FW-190", "Destroyed"], ["18 August 1944", "20 miles northeast of Paris, France", "Air", "0.5", "Me-109", "Destroyed"], ["24 April 1944", "South of Munich, Germany", "Air", "3", "Me-110", "Destroyed"], ["16 March 1944", "20 miles south of Stuttgart, Germany", "Air", "1", "Me-110", "Destroyed"], ["13 September 1944", "South of Nordhausen, Germany", "Air", "2.5", "Me-109", "Destroyed"], ["8 March 1944", "Near Steinhuder Meer (Lake), Germany", "Air", "1", "Me-109", "Destroyed"], ["11 April 1944", "20 miles northeast of Magdeburg, Germany", "Air", "0.5", "Me-109", "Destroyed"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Damaged"], ["14 January 1945", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Destroyed"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "2", "Me-109", "Destroyed"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what type of plane was encountered the least?
|
Mig-15
|
Answer:
| 128
|
Table InputTable: [["Name", "Sport", "Event", "Placing", "Performance"], ["David Berger", "Weightlifting", "Light-heavyweight <82.5 kg", "—", "J:132.5 C:122.5 S:— T:—"], ["Yair Michaeli", "Sailing", "Flying Dutchman", "23", "28-22-22-19-25-19-DNS = 171 pts\\n(left Kiel before 7th race)"], ["Gad Tsobari", "Wrestling", "Freestyle — Light Flyweight <48 kg", "Group stage", "0W–2L"], ["Yehuda Weissenstein", "Fencing", "Men's foil", "Second round", "W2–L8 (1R 2-3, 2R 0-5)"], ["Dan Alon", "Fencing", "Men's foil", "Second round", "W5–L5 (1R 3-2, 2R 2-3)"], ["Itzhak Nir", "Sailing", "Flying Dutchman", "23", "28-22-22-19-25-19-DNS = 171 pts\\n(left Kiel before 7th race)"], ["Eliezer Halfin", "Wrestling", "Freestyle — Lightweight <68 kg", "Group stage", "1W–2L"], ["Esther Shahamorov", "Athletics", "Women's 100 m hurdles", "Semifinal", "Did not start (left Munich before the semifinal)"], ["Yossef Romano", "Weightlifting", "Middleweight <75 kg", "—", "(retired injured on third attempt to press 137.5kg)"], ["Esther Shahamorov", "Athletics", "Women's 100 m", "Semifinal (5th)", "11.49"], ["Ze'ev Friedman", "Weightlifting", "Bantamweight <56 kg", "12", "J:102.5 C:102.5 S:125 T:330"], ["Shaul Ladani", "Athletics", "Men's 50 km walk", "19", "4:24:38.6\\n(also entered for 20 km walk, but did not start)"], ["Mark Slavin", "Wrestling", "Greco-Roman — Middleweight <82 kg", "—", "(taken hostage before his scheduled event)"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the top placing competitor?
|
Esther Shahamorov
|
Answer:
| 128
|
Table InputTable: [["Result", "Date", "Category", "Tournament", "Surface", "Partnering", "Opponents", "Score"], ["Runner-up", "23 April 1984", "$200,000", "Orlando, United States", "Clay", "Wendy Turnbull", "Claudia Kohde-Kilsch\\n Hana Mandlíková", "0–6, 6–1, 3–6"], ["Runner-up", "16 April 1984", "$200,000", "Hilton Head, United States", "Clay", "Sharon Walsh", "Claudia Kohde-Kilsch\\n Hana Mandlíková", "5–7, 2–6"], ["Winner", "13 June 1982", "$100,000", "Birmingham, Great Britain", "Grass", "Jo Durie", "Rosie Casals\\n Wendy Turnbull", "6–3, 6–2"], ["Winner", "20 November 1983", "$150,000", "Brisbane, Australia", "Grass", "Wendy Turnbull", "Pam Shriver\\n Sharon Walsh", "6–3, 6–4"], ["Winner", "23 May 1983", "$150,000", "Berlin, Germany", "Carpet", "Jo Durie", "Claudia Kohde-Kilsch\\n Eva Pfaff", "6–4, 7–6(7–2)"], ["Runner-up", "29 January 1984", "$100,000", "Marco Island, United States", "Clay", "Andrea Jaeger", "Hana Mandlíková\\n Helena Suková", "6–3, 2–6, 2–6"], ["Runner-up", "22 April 1984", "$250,000", "Amelia Island, United States", "Clay", "Mima Jaušovec", "Kathy Jordan\\n Anne Smith", "4–6, 6–3, 4–6"], ["Runner-up", "20 May 1985", "$75,000", "Melbourne, Australia", "Carpet", "Kathy Jordan", "Pam Shriver\\n Liz Smylie", "2–6, 7–5, 1–6"], ["Winner", "27 November 1983", "$150,000", "Sydney, Australia", "Grass", "Wendy Turnbull", "Hana Mandlíková\\n Helena Suková", "6–4, 6–3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:is the price money for 23 january 1984 more than that of 23 april 1984?
|
no
|
Answer:
| 128
|
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2011", "5 Mar 2011", "Kranjska Gora, Slovenia", "Giant Slalom", "", "", "", ""], ["2010", "6 Dec 2009", "Beaver Creek, USA", "Giant Slalom", "", "", "", ""], ["2010", "12 Mar 2010", "Garmisch, Germany", "Giant Slalom", "", "", "", ""], ["2009", "13 Dec 2008", "Val d'Isère, France", "Giant slalom", "", "", "", ""], ["2010", "10 Mar 2010", "Garmisch, Germany", "Downhill", "", "", "", ""], ["2010", "16 Jan 2010", "Wengen, Switzerland", "Downhill", "", "", "", ""], ["Season", "Date", "Location", "Race", "", "", "", ""], ["2010", "4 Dec 2009", "Beaver Creek, USA", "Super Combined", "", "", "", ""], ["2010", "5 Dec 2009", "Beaver Creek, USA", "Downhill", "", "", "", ""], ["2009", "16 Jan 2009", "Wengen, Switzerland", "Super Combined", "", "", "", ""], ["2011", "24", "3", "–", "5", "6", "9", "6"], ["2008", "21", "64", "–", "28", "46", "46", "31"], ["2012", "25", "24", "–", "16", "28", "17", "19"], ["2009", "22", "7", "–", "6", "16", "16", "1"], ["2010", "23", "1", "–", "2", "6", "2", "2"], ["2013", "26", "48", "–", "48", "27", "38", "4"], ["2007", "20", "130", "–", "40", "–", "–", "—"], ["2014", "27", "18", "–", "25", "14", "20", "11"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the only race in 2011?
|
Giant Slalom
|
Answer:
| 128
|
Table InputTable: [["Round", "Pick", "Name", "Position", "College"], ["6", "170", "Frank Murphy", "WR", "Kansas State"], ["7", "254", "Michael Green", "S", "Northwestern State"], ["2", "39", "Mike Brown", "S", "Nebraska"], ["6", "174", "Paul Edinger", "K", "Michigan State"], ["3", "69", "Dez White", "WR", "Georgia Tech"], ["1", "9", "Brian Urlacher", "S", "New Mexico"], ["3", "87", "Dustin Lyman", "TE", "Wake Forest"], ["4", "125", "Reggie Austin", "DB", "Wake Forest"], ["7", "223", "James Cotton", "DE", "Ohio State"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which position was listed the most on this chart?
|
S
|
Answer:
| 128
|
Table InputTable: [["Number", "Name", "Term Started", "Term Ended", "Alma Mater", "Field(s)", "Educational Background"], ["5", "Dr M. Shafi Ahmad", "1989", "1990", "University of London", "Astronomy", "Ph.D"], ["9", "Major General Ahmed Bilal", "2010", "Present", "Pakistan Army Corps of Signals Engineering", "Computer Engineering", "Master of Science (M.S)"], ["7", "Dr Abdul Majid", "1997", "2001", "University of Wales", "Astrophysics", "Ph.D"], ["3", "Air Commodore K. M. Ahmad", "1979", "1980", "Pakistan Air Force Academy", "Flight Instructor", "Certificated Flight Instructor (CFI)"], ["1", "Dr Abdus Salam", "1961", "1967", "Imperial College", "Theoretical Physics", "Doctor of Philosophy (Ph.D)"], ["8", "Major General Raza Hussain", "2001", "2010", "Pakistan Army Corps of Electrical and Mechanical Engineers", "Electrical Engineering", "B.S."], ["6", "Engr.Sikandar Zaman", "1990", "1997", "University of Leeds", "Mechanical Engineering", "Bachelor of Science (B.S.)"], ["4", "Dr Salim Mehmud", "1980", "1989", "Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory", "Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering", "Ph.D"], ["2", "Air Commodore Dr Władysław Turowicz", "1967", "1979", "Warsaw University of Technology", "Aeronautical Engineering", "Ph.D"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:m. shafi ahmad and absdul majid both had what type of degree?
|
Ph.D
|
Answer:
| 128
|
Table InputTable: [["Ship", "Hull No.", "Status", "Years Active", "NVR\\nPage"], ["Guadalupe", "T-AO-200", "Active", "1992–present", "AO200"], ["Patuxent", "T-AO-201", "Active", "1995–present", "AO201"], ["Big Horn", "T-AO-198", "Active", "1992–present", "AO198"], ["Laramie", "T-AO-203", "Active", "1996–present", "AO203"], ["Pecos", "T-AO-197", "Active", "1990–present", "AO197"], ["Tippecanoe", "T-AO-199", "Active", "1993–present", "AO199"], ["Kanawha", "T-AO-196", "Active", "1991–present", "AO196"], ["Yukon", "T-AO-202", "Active", "1994–present", "AO202"], ["Rappahannock", "T-AO-204", "Active", "1995–present", "AO204"], ["Leroy Grumman", "T-AO-195", "Active", "1989–present", "AO195"], ["John Lenthall", "T-AO-189", "Active", "1987-1996; 1998–present", "AO189"], ["Walter S. Diehl", "T-AO-193", "Active", "1988–present", "AO193"], ["John Ericsson", "T-AO-194", "Active", "1991–present", "AO194"], ["Benjamin Isherwood", "T-AO-191", "Cancelled when 95.3% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011", "Launched 1988, christened 1991, never in service", "AO191"], ["Henry Eckford", "T-AO-192", "Cancelled when 84% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011", "Launched 1989, never in service", "AO192"], ["Andrew J. Higgins", "T-AO-190", "Inactivated May 1996. Sold to the Chilean Navy May 2009. Towed to Atlantic Marine Alabama shipyard, Mobile, Alabama, September 2009 for three-month refit. Commissioned in Chilean Navy on 10 February 2010 and renamed Almirante Montt.[1]", "1987-1996 (USA); 2010–present (Chile)", "AO190"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many photos total are listed?
|
18
|
Answer:
| 128
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2001", "World Championships", "Edmonton, Canada", "18th (sf)", "400 m hurdles", "49.80"], ["2007", "World Championships", "Osaka, Japan", "3rd", "4x400 m relay", "3:00.05"], ["2007", "World Championships", "Osaka, Japan", "3rd", "400 m hurdles", "48.12 (NR)"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "400 m", "45.39 (CR, NR)"], ["2001", "Universiade", "Beijing, China", "8th", "400 m hurdles", "49.68"], ["2008", "Olympic Games", "Beijing, China", "6th", "400 m hurdles", "48.42"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "4x400 m relay", "3:05.50 (CR)"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "3rd", "4x400 m relay", "3:06.61"], ["2004", "Olympic Games", "Athens, Greece", "6th", "400 m hurdles", "49.00"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "400 m hurdles", "49.23"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "7th (sf)", "400 m", "46.82"], ["2002", "European Championships", "Munich, Germany", "4th", "400 m", "45.40"], ["2008", "Olympic Games", "Beijing, China", "7th", "4x400 m relay", "3:00.32"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "400 m hurdles", "48.45"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "4x400 m relay", "3:03.32"], ["2004", "Olympic Games", "Athens, Greece", "10th (h)", "4x400 m relay", "3:03.69"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was first listed as the position according to this chart?
|
5
|
Answer:
| 128
|
Table InputTable: [["Represent", "Candidate", "in Russian", "Age", "Height", "Hometown"], ["Adygean Republic", "Alissa Joanndova", "Алисса Йоанндова", "19", "1.83 m (6 ft 0 in)", "Tulsky"], ["Altai Krai", "Anastasija Nindova", "Анастасия Ниндова", "22", "1.74 m (5 ft 8 1⁄2 in)", "Barnaul"], ["Chuvash Republic", "Martha Neosova", "Мартха Неосова", "19", "1.78 m (5 ft 10 in)", "Cheboksary"], ["North Ossetian Republic", "Emilianna Ninn", "Емилианна Нинн", "22", "1.76 m (5 ft 9 1⁄2 in)", "Vladikavkaz"], ["Mordovian Republic", "Olga Stepančenko", "Олга Степанченко", "20", "1.75 m (5 ft 9 in)", "Saransk"], ["Perm Krai", "Svetlana Ninkova", "Светлана Нинкова", "22", "1.73 m (5 ft 8 in)", "Perm"], ["Krasnodar Krai", "Patricia Valiahmetova", "Патрициа Валиахметова", "20", "1.80 m (5 ft 11 in)", "Krasnodar"], ["Nenets Okrug", "Sofia Meldemendev", "Софиа Мелдемендев", "25", "1.85 m (6 ft 1 in)", "Naryan-Mar"], ["Chukotka Okrug", "Mariesea Mnesiču", "Мариесеа Мнесичу", "19", "1.80 m (5 ft 11 in)", "Anadyr"], ["Tuva Republic", "Azida Levenok", "Азида Левенок", "18", "1.81 m (5 ft 11 1⁄2 in)", "Kyzyl"], ["Bashkortostan Republic", "Aimee Neosaranova", "Аимее Неосаранова", "19", "1.77 m (5 ft 9 1⁄2 in)", "Ufa"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the the candidate before anastasija nindova?
|
Alissa Joanndova
|
Answer:
| 128
|
Table InputTable: [["Season", "Episodes", "Season Premiere", "Season Finale"], ["5", "40", "October 12, 2009", "June 14, 2010"], ["3", "44", "October 15, 2007", "June 2, 2008"], ["6", "20", "September 6, 2010", "December 6, 2010"], ["2", "52", "October 7, 2006", "July 16, 2007"], ["4", "48", "October 13, 2008", "May 11, 2009"], ["1", "20", "March 4, 2006", "May 13, 2006"], ["7", "8", "October 29, 2013", "December 17, 2013"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what date is next listed after june 14, 2010.
|
December 6, 2010
|
Answer:
| 128
|
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Partner", "Opponents", "Score"], ["Winner", "1.", "13 February 2011", "Rancho Mirage, United States", "Hard", "Karolína Plíšková", "Nadejda Guskova\\n Sandra Zaniewska", "6–7(6–8), 6–1, 6–4"], ["Winner", "2.", "7 August 2011", "Vancouver, Canada", "Hard", "Karolína Plíšková", "Jamie Hampton\\n N. Lertcheewakarn", "5–7, 6–2, 6–4"], ["Winner", "3.", "23 January 2012", "Andrézieux-Bouthéon, France", "Hard (i)", "Karolína Plíšková", "Julie Coin\\n Eva Hrdinová", "6–4, 4–6, [10–5]"], ["Winner", "4.", "30 January 2012", "Grenoble, France", "Hard (i)", "Karolína Plíšková", "Valentyna Ivakhnenko\\n Maryna Zanevska", "6–1, 6–3"], ["Runner-up", "2.", "6 November 2011", "Taipei 5, Taiwan", "Hard", "Karolína Plíšková", "Chan Yung-jan\\n Zheng Jie", "6–7(5–7), 7–5, 3–6"], ["Winner", "5.", "12 November 2012", "Zawada, Poland", "Carpet (i)", "Karolína Plíšková", "Kristina Barrois\\n Sandra Klemenschits", "6–3, 6–1"], ["Runner-up", "1.", "16 May 2010", "Kurume, Japan", "Clay", "Karolína Plíšková", "Sun Shengnan\\n Xu Yifan", "0–6, 3–6"], ["Winner", "6.", "28 October 2013", "Barnstaple, United Kingdom", "Hard (i)", "Naomi Broady", "Raluca Olaru\\n Tamira Paszek", "6–3, 3–6, [10–5]"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was a tournament held in the united states?
|
1
|
Answer:
| 128
|
Table InputTable: [["Pos", "No.", "Driver", "Team", "Laps", "Time/Retired", "Grid", "Laps Led", "Points"], ["17", "20", "Ed Carpenter", "Vision Racing", "84", "+ 1 Lap", "21", "0", "13"], ["1", "9", "Scott Dixon", "Chip Ganassi Racing", "85", "1:46:05.7985", "3", "51", "52"], ["19", "7", "Danica Patrick", "Andretti Green Racing", "83", "+ 2 Laps", "12", "0", "12"], ["15", "13", "E. J. Viso", "HVM Racing", "84", "+ 1 Lap", "9", "0", "15"], ["16", "4", "Dan Wheldon", "Panther Racing", "84", "+ 1 Lap", "17", "0", "14"], ["13", "18", "Justin Wilson", "Dale Coyne Racing", "85", "+ 53.5768", "2", "28", "17"], ["14", "33", "Robert Doornbos (R)", "HVM Racing", "85", "+ 1:10.0812", "18", "0", "16"], ["7", "5", "Paul Tracy", "KV Racing Technology", "85", "+ 49.7020", "10", "0", "26"], ["20", "24", "Mike Conway (R)", "Dreyer & Reinbold Racing", "69", "Mechanical", "16", "0", "12"], ["18", "98", "Richard Antinucci", "Team 3G", "83", "+ 2 Laps", "19", "0", "12"], ["8", "02", "Graham Rahal", "Newman/Haas/Lanigan Racing", "85", "+ 50.4517", "4", "0", "24"], ["6", "26", "Marco Andretti", "Andretti Green Racing", "85", "+ 46.7669", "13", "0", "28"], ["12", "3", "Hélio Castroneves", "Penske Racing", "85", "+ 53.2362", "5", "0", "18"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers have no laps led?
|
18
|
Answer:
| 128
|
Table InputTable: [["Position", "Officer", "current officers", "superseded by", "Royal Household"], ["6", "Lord Great Chamberlain", "The Marquess of Cholmondeley", "Lord High Treasurer", "Lord Chamberlain"], ["2", "Lord High Chancellor", "The Rt Hon Chris Grayling, MP", "", ""], ["1", "Lord High Steward", "vacant", "Justiciar", "Lord Steward"], ["9", "Lord High Admiral", "HRH The Duke of Edinburgh", "", ""], ["3", "Lord High Treasurer", "in commission", "", ""], ["7", "Lord High Constable", "vacant", "Earl Marshal", "Master of the Horse"], ["4", "Lord President of the Council", "The Rt Hon Nick Clegg, MP", "", ""], ["5", "Lord Privy Seal", "The Rt Hon Andrew Lansley, CBE, MP", "", ""], ["8", "Earl Marshal", "The Duke of Norfolk", "", "Master of the Horse"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who superceded lord high steward?
|
Justiciar
|
Answer:
| 128
|
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Partner", "Opponents", "Score"], ["Winner", "1.", "13 February 2011", "Rancho Mirage, United States", "Hard", "Karolína Plíšková", "Nadejda Guskova\\n Sandra Zaniewska", "6–7(6–8), 6–1, 6–4"], ["Runner-up", "3.", "20 November 2011", "Bratislava, Slovakia", "Hard", "Karolína Plíšková", "Naomi Broady\\n Kristina Mladenovic", "7–5, 4–6, [2–10]"], ["Runner-up", "4.", "17 September 2012", "Shrewsbury, United Kingdom", "Hard (i)", "Karolína Plíšková", "Vesna Dolonc\\n Stefanie Vögele", "1–6, 7–6(7–3), [13–15]"], ["Winner", "4.", "30 January 2012", "Grenoble, France", "Hard (i)", "Karolína Plíšková", "Valentyna Ivakhnenko\\n Maryna Zanevska", "6–1, 6–3"], ["Winner", "5.", "12 November 2012", "Zawada, Poland", "Carpet (i)", "Karolína Plíšková", "Kristina Barrois\\n Sandra Klemenschits", "6–3, 6–1"], ["Winner", "3.", "23 January 2012", "Andrézieux-Bouthéon, France", "Hard (i)", "Karolína Plíšková", "Julie Coin\\n Eva Hrdinová", "6–4, 4–6, [10–5]"], ["Winner", "2.", "7 August 2011", "Vancouver, Canada", "Hard", "Karolína Plíšková", "Jamie Hampton\\n N. Lertcheewakarn", "5–7, 6–2, 6–4"], ["Runner-up", "2.", "6 November 2011", "Taipei 5, Taiwan", "Hard", "Karolína Plíšková", "Chan Yung-jan\\n Zheng Jie", "6–7(5–7), 7–5, 3–6"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was kristyna pliskova's partner in her first professional doubles tournament?
|
Karolína Plíšková
|
Answer:
| 128
|
Table InputTable: [["Pick #", "NFL Team", "Player", "Position", "College"], ["3", "Baltimore Colts", "Alan Ameche", "Fullback", "Wisconsin"], ["9", "Philadelphia Eagles", "Dick Bielski", "Fullback", "Maryland"], ["12", "Detroit Lions", "Dave Middleton", "Halfback", "Auburn"], ["8", "New York Giants", "Joe Heap", "Halfback", "Notre Dame"], ["6", "Pittsburgh Steelers", "Frank Varrichione", "Tackle", "Notre Dame"], ["5", "Green Bay Packers", "Tom Bettis", "Guard", "Purdue"], ["10", "San Francisco 49ers", "Dickey Moegle", "Halfback", "Rice"], ["1", "Baltimore Colts (Lottery bonus pick)", "George Shaw", "Quarterback", "Oregon"], ["11", "Chicago Bears", "Ron Drzewiecki", "Halfback", "Marquette"], ["7", "Los Angeles Rams", "Larry Morris", "Center", "Georgia Tech"], ["2", "Chicago Cardinals", "Max Boydston", "End", "Oklahoma"], ["4", "Washington Redskins", "Ralph Guglielmi", "Quarterback", "Notre Dame"], ["13", "Cleveland Browns", "Kurt Burris", "Center", "Oklahoma"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many fullback positions were picked?
|
2
|
Answer:
| 128
|
Table InputTable: [["Year", "Injuries (US $000)", "Deaths (age <15)", "CPSC toy safety funding\\n(US$ Millions)", "Toy sales\\n(US $ Billions)"], ["1997", "141", "", "", ""], ["1996", "130", "", "", ""], ["1995", "139", "", "", ""], ["1998", "153", "14", "", ""], ["1994", "154", "", "", ""], ["2009", "no data", "12", "no data", ""], ["2008", "no data", "19", "no data", ""], ["2007", "no data", "22", "no data", ""], ["2005", "202 (estimate)", "20", "11.0", "22.2"], ["1999", "152", "16", "13.6", ""], ["2006", "no data", "22", "no data†", "22.3"], ["2001", "255", "25", "12.4", ""], ["2004", "210", "16", "11.5", "22.4"], ["2000", "191", "17", "12.0", ""], ["2003", "206", "11", "12.8", "20.7"], ["2002", "212", "13", "12.2", "21.3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which year had the least amount of toy sales?
|
2003
|
Answer:
| 128
|
Table InputTable: [["Network name", "Flagship", "Programming type", "Owner", "Affiliates"], ["Azteca 13", "XHDF 13", "news, soap operas, and sports", "TV Azteca", "4"], ["Azteca 7", "XHIMT 7", "sports, series, and movies", "TV Azteca", "5"], ["Galavisión", "XEQ 9", "retro programming and sports", "Televisa", "1"], ["Canal de las Estrellas", "XEW 2", "soap operas, retro movies and sports", "Televisa", "10"], ["Canal 5", "XHGC 5", "cartoons, movies, and series", "Televisa", "4"], ["TV 10 Chiapas", "XHTTG", "educational", "Gobierno del Estado de Chiapas", "7"], ["Independent", "", "varies", "Independent", "3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many affiliates does tv azteca have all together?
|
9
|
Answer:
| 128
|
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs"], ["2005", "1", "USL W-League", "6th, Western", ""], ["2006", "1", "USL W-League", "5th, Western", ""], ["2003", "2", "USL W-League", "5th, Western", ""], ["2007", "1", "USL W-League", "5th, Western", ""], ["2009", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2008", "1", "USL W-League", "6th, Western", "Did not qualify"], ["2010", "1", "USL W-League", "6th, Western", "Did not qualify"], ["2012", "1", "USL W-League", "4th, Western", "Did not qualify"], ["2011", "1", "USL W-League", "7th, Western", "Did not qualify"], ["2013", "1", "USL W-League", "4th, Western", "Did not qualify"], ["2004", "1", "USL W-League", "8th, Western", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the number of times that the team placed 5th?
|
3
|
Answer:
| 128
|
Table InputTable: [["Week", "Date", "Opponent", "Score", "Result", "Record"], ["10", "Oct 30", "vs. Hamilton Tiger-Cats", "30–9", "Loss", "1–11"], ["1", "Aug 28", "at Toronto Argonauts", "13–6", "Loss", "0–1"], ["6", "Oct 2", "at Hamilton Tiger-Cats", "45–0", "Loss", "1–6"], ["4", "Sept 18", "vs. Toronto Argonauts", "34–6", "Loss", "1–4"], ["8", "Oct 16", "vs. Toronto Argonauts", "27–11", "Loss", "1–9"], ["11", "Nov 6", "at Toronto Argonauts", "18–12", "Loss", "1–12"], ["12", "Nov 13", "vs. Montreal Alouettes", "14–12", "Win", "2–12"], ["5", "Sept 25", "vs. Hamilton Tiger-Cats", "38–12", "Loss", "1–5"], ["3", "Sept 11", "at Toronto Argonauts", "12–5", "Win", "1–3"], ["2", "Sept 4", "at Montreal Alouettes", "21–2", "Loss", "0–2"], ["9", "Oct 23", "at Hamilton Tiger-Cats", "25–17", "Loss", "1–10"], ["7", "Oct 11", "at Montreal Alouettes", "24–6", "Loss", "1–8"], ["7", "Oct 9", "vs. Montreal Alouettes", "25–11", "Loss", "1–7"], ["2", "Sept 6", "vs. Montreal Alouettes", "20–11", "Loss", "0–3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many games did the team score at least 30 points?
|
4
|
Answer:
| 128
|
Table InputTable: [["Year", "Car", "Start", "Qual", "Rank", "Finish", "Laps", "Led", "Retired"], ["1928", "8", "4", "117.031", "4", "10", "200", "33", "Running"], ["1927", "27", "27", "107.765", "22", "3", "200", "0", "Running"], ["1938", "17", "4", "122.499", "6", "17", "130", "0", "Rod"], ["1926", "31", "12", "102.789", "13", "11", "142", "0", "Flagged"], ["1937", "38", "7", "118.788", "16", "8", "200", "0", "Running"], ["1939", "62", "27", "121.749", "24", "11", "200", "0", "Running"], ["1933", "34", "12", "113.578", "15", "7", "200", "0", "Running"], ["1929", "23", "11", "112.146", "15", "17", "91", "0", "Supercharger"], ["1931", "37", "19", "111.725", "6", "18", "167", "0", "Crash T4"], ["1934", "8", "7", "113.733", "13", "17", "94", "0", "Rod"], ["1932", "25", "20", "108.896", "34", "13", "184", "0", "Flagged"], ["1930", "9", "20", "100.033", "18", "20", "79", "0", "Valve"], ["1935", "44", "6", "115.459", "11", "21", "102", "0", "Magneto"], ["Totals", "Totals", "Totals", "Totals", "Totals", "Totals", "1989", "33", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did he race more laps in 1926 or 1938?
|
1926
|
Answer:
| 128
|
Table InputTable: [["Iteration", "Dates", "Location", "Attendance", "Notes"], ["GameStorm 15", "March 21–24, 2013", "Hilton - Vancouver, WA", "1188", ""], ["GameStorm 10", "March 2008", "Red Lion - Vancouver, WA", "750", "-"], ["GameStorm 13", "March 24–27, 2011", "Hilton - Vancouver, WA", "984", "Guests: Lisa Steenson, Michael A. Stackpole"], ["GameStorm 12", "March 25–28, 2010", "Hilton - Vancouver, WA", "802", "Board games Guest of Honor: Tom Lehmann"], ["GameStorm 11", "March 26–29, 2009", "Hilton - Vancouver, WA", "736", "debut of Video games, first-ever Artist Guest of Honor, Rob Alexander"], ["GameStorm 14", "March 22–25, 2012", "Hilton - Vancouver, WA", "1072", "Boardgame:Andrew Hackard and Sam Mitschke of Steve Jackson Games - RPG: Jason Bulmahn"], ["GameStorm 16", "March 20–23, 2014", "Hilton - Vancouver, WA", "tba", "Guests: Mike Selinker, Shane Lacy Hensley, Lisa Steenson, Zev Shlasinger of Z-Man Games"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the total attendance for gamestorm 11?
|
736
|
Answer:
| 128
|
Table InputTable: [["Pos", "No.", "Driver", "Team", "Engine", "Laps", "Time/Retired", "Grid", "Laps Led", "Points"], ["13", "9", "Scott Dixon", "Chip Ganassi Racing", "Honda", "84", "+ 1 lap", "5", "0", "17"], ["11", "18", "Justin Wilson", "Dale Coyne Racing", "Honda", "84", "+ 1 lap", "20", "0", "19"], ["7", "77", "Simon Pagenaud (R)", "Schmidt Hamilton Motorsports", "Honda", "85", "+ 12.3087", "9", "0", "26"], ["26", "27", "James Hinchcliffe", "Andretti Autosport", "Chevrolet", "35", "Mechanical", "10", "0", "10"], ["21", "83", "Charlie Kimball", "Chip Ganassi Racing", "Honda", "82", "+ 3 laps", "21", "0", "12"], ["12", "19", "James Jakes", "Dale Coyne Racing", "Honda", "84", "+ 1 lap", "24", "0", "18"], ["18", "28", "Ryan Hunter-Reay", "Andretti Autosport", "Chevrolet", "84", "+ 1 lap", "7", "1", "12"], ["5", "38", "Graham Rahal", "Chip Ganassi Racing", "Honda", "85", "+ 9.4667", "13", "0", "30"], ["20", "20", "Ed Carpenter", "Ed Carpenter Racing", "Chevrolet", "84", "+ 1 lap", "25", "0", "12"], ["27", "15", "Takuma Sato", "Rahal Letterman Lanigan Racing", "Honda", "2", "Mechanical", "26", "0", "10"], ["14", "14", "Mike Conway", "A.J. Foyt Enterprises", "Honda", "84", "+ 1 lap", "14", "0", "16"], ["10", "11", "Tony Kanaan", "KV Racing Technology", "Chevrolet", "84", "+ 1 lap", "16", "0", "20"], ["24", "6", "Katherine Legge (R)", "Dragon Racing", "Chevrolet", "48", "Mechanical", "19", "0", "12"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the next driver listed after scott dixon?
|
Mike Conway
|
Answer:
| 128
|
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event"], ["2004", "Olympic Games", "Athens, Greece", "3rd", "100 m hurdles"], ["2003", "World Indoor Championships", "Birmingham, England", "3rd", "60 m hurdles"], ["1997", "World Indoor Championships", "Paris, France", "5th", "60 m hurdles"], ["2000", "Olympic Games", "Sydney, Australia", "3rd", "100 m hurdles"], ["2000", "Grand Prix Final", "Doha, Qatar", "4th", "100 m hurdles"], ["1997", "USA Outdoor Championships", "Indianapolis, United States", "1st", "100 m hurdles"], ["2002", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["2003", "World Athletics Final", "Monaco", "6th", "100 m hurdles"], ["1998", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["1999", "World Indoor Championships", "Maebashi, Japan", "6th", "60 m hurdles"], ["2002", "Grand Prix Final", "Paris, France", "7th", "100 m hurdles"], ["1998", "Grand Prix Final", "Moscow, Russia", "2nd", "100 m hurdles"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which venue did melissa morrison compete at in 2004?
|
Athens, Greece
|
Answer:
| 128
|
Table InputTable: [["Year", "Recipient", "Nationality", "Profession", "Speech"], ["2001", "Cynthia Ozick", "United States", "Professional writer", ""], ["2005", "William Safire", "United States", "Author, journalist and speechwriter\\n1978 Pulitzer Prize winner", ""], ["2000", "Sir Martin Gilbert", "United Kingdom", "Historian and writer", ""], ["2007", "Norman Podhoretz", "United States", "Author, columnist", ""], ["1997", "Elie Wiesel", "United States", "Professional writer\\nWinner of the Nobel Peace Prize (1986)", ""], ["2004", "Arthur Cohn", "Switzerland", "Filmmaker and writer", ""], ["2002", "Charles Krauthammer", "United States", "The Washington Post columnist", "[1]"], ["2006", "Daniel Pipes", "United States", "Author and historian", ""], ["1998", "Herman Wouk", "United States", "Professional writer and 1952 Pulitzer Prize winner", ""], ["1999", "A.M. Rosenthal", "United States", "Former New York Times editor\\nFormer New York Daily News columnist", ""], ["2009", "Caroline Glick", "Israel", "Journalist", ""], ["2008", "David Be'eri, Mordechai Eliav, Rabbi Yehuda Maly", "Israel", "", ""], ["2003", "Ruth Roskies Wisse", "United States", "Yiddish professor of Harvard University", "[2]"], ["2010", "Malcolm Hoenlein", "United States", "Executive Vice Chairman of the Conference of Presidents of Major American Jewish Organizations", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times is professional writer listed as the profession according to this chart?
|
3
|
Answer:
| 128
|
Table InputTable: [["", "Name on the Register", "Date listed", "Location", "City or town", "Summary"], ["13", "Jenness Farm", "March 2, 2001\\n(#01000206)", "626 Pickering Rd.\\n43°14′36″N 70°56′12″W / 43.243333°N 70.936667°W", "Rochester", ""], ["24", "Rochester Commercial and Industrial District", "April 8, 1983\\n(#83001154)", "N. Main, Wakefield, Hanson, and S. Main Sts. and Central Square\\n43°18′11″N 70°58′34″W / 43.303056°N 70.976111°W", "Rochester", ""], ["5", "Farmington Town Pound", "September 2, 1993\\n(#93000884)", "Northwestern side of Pound Rd. 300 ft (91 m) north of the junction of Ten Rod Rd.\\n43°21′33″N 71°04′49″W / 43.359167°N 71.080278°W", "Farmington", ""], ["12", "Richard Hayes House", "February 27, 1986\\n(#86000283)", "184 Gonic Rd.\\n43°15′38″N 70°58′44″W / 43.260556°N 70.978889°W", "Rochester", ""], ["36", "US Post Office-Somersworth Main", "July 17, 1986\\n(#86002246)", "2 Elm St.\\n43°15′33″N 70°52′18″W / 43.259167°N 70.871667°W", "Somersworth", ""], ["21", "Queensbury Mill", "April 10, 1987\\n(#86003362)", "1 Market St.\\n43°15′54″N 70°51′58″W / 43.265°N 70.866111°W", "Somersworth", ""], ["29", "Sawyer Woolen Mills", "September 13, 1989\\n(#89001208)", "1 Mill St.\\n43°10′44″N 70°52′35″W / 43.178889°N 70.876389°W", "Dover", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of listings from barrington, farmington, and rochester combined?
|
5
|
Answer:
| 128
|
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2006", "Spartak Nizhny Novgorod", "Russia", "2", "36", "1"], ["2006/07", "Dnipro Dnipropetrovsk", "Ukraine", "1", "12", "0"], ["2005", "CSKA Moscow", "Russia", "1", "0", "0"], ["2004", "CSKA Moscow", "Russia", "1", "0", "0"], ["2011/12", "Dnipro Dnipropetrovsk", "Ukraine", "1", "16", "0"], ["2007/08", "Dnipro Dnipropetrovsk", "Ukraine", "1", "24", "0"], ["2010/11", "Dnipro Dnipropetrovsk", "Ukraine", "1", "23", "0"], ["2012/13", "Lokomotiv Moscow", "Russia", "1", "8", "0"], ["2009/10", "Dnipro Dnipropetrovsk", "Ukraine", "1", "28", "0"], ["2012/13", "Dnipro Dnipropetrovsk", "Ukraine", "1", "10", "1"], ["2008/09", "Dnipro Dnipropetrovsk", "Ukraine", "1", "22", "1"], ["2013/14", "Lokomotiv Moscow", "Russia", "1", "14", "1"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many teams did not score any goals in the 2006 season?
|
1
|
Answer:
| 128
|
Table InputTable: [["Pos", "Rider", "Manufactuer", "Time/Retired", "Points"], ["23", "Bernard Haenggeli", "Aprilia", "+2:41.806", ""], ["19", "Paolo Casoli", "Gilera", "+1:26.061", ""], ["18", "Bernd Kassner", "Aprilia", "+1:16:464", ""], ["16", "Frédéric Protat", "Aprilia", "+1:15.858", ""], ["14", "Jean-Michel Bayle", "Aprilia", "+1:15.546", "2"], ["Ret", "Jurgen van den Goorbergh", "Aprilia", "Retirement", ""], ["Ret", "Patrick van den Goorbergh", "Aprilia", "Retirement", ""], ["8", "Jean-Philippe Ruggia", "Aprilia", "+3.985", "8"], ["Ret", "Andreas Preining", "Aprilia", "Retirement", ""], ["5", "Loris Reggiani", "Aprilia", "+2.411", "11"], ["Ret", "Jean-Pierre Jeandat", "Aprilia", "Retirement", ""], ["1", "Doriano Romboni", "Honda", "33:53.776", "25"], ["Ret", "Luis Maurel", "Aprilia", "Retirement", ""], ["12", "John Kocinski", "Suzuki", "+25.463", "4"], ["Ret", "Wilco Zeelenberg", "Aprilia", "Retirement", ""], ["20", "Gabriele Debbia", "Honda", "+1:40.049", ""], ["24", "Alessandro Gramigni", "Gilera", "+1 Lap", ""], ["2", "Loris Capirossi", "Honda", "+0.090", "20"], ["22", "Massimo Pennacchioli", "Honda", "+1:59.498", ""], ["15", "Juan Borja", "Honda", "+1:15.769", "1"], ["21", "Adrian Bosshard", "Honda", "+1:47.492", ""], ["11", "Alberto Puig", "Honda", "+25.136", "5"], ["9", "Carlos Cardús", "Honda", "+4.893", "7"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who came in first?
|
Doriano Romboni
|
Answer:
| 128
|
Table InputTable: [["Team", "Stadium", "Capacity", "City/Area"], ["Widnes Vikings (2014 season)", "The Select Security Stadium", "13,500", "Widnes, Cheshire, England"], ["Wigan Warriors (2014 season)", "DW Stadium", "25,138", "Wigan, Greater Manchester"], ["Warrington Wolves (2014 season)", "Halliwell Jones Stadium", "15,500", "Warrington, Cheshire"], ["Bradford Bulls (2014 season)", "Provident Stadium", "27,000", "Bradford, West Yorkshire"], ["Catalans Dragons (2014 season)", "Stade Gilbert Brutus", "14,000", "Perpignan, Pyrénées-Orientales, France"], ["Hull Kingston Rovers (2014 season)", "MS3 Craven Park", "9,471", "Kingston upon Hull, East Riding of Yorkshire"], ["Salford City Reds (2014 season)", "Salford City Stadium", "12,000", "Salford, Greater Manchester"], ["Leeds Rhinos (2014 season)", "Headingley Carnegie Stadium", "22,250", "Leeds, West Yorkshire"], ["London Broncos (2014 season)", "Twickenham Stoop", "12,700", "Twickenham, London"], ["Wakefield Trinity Wildcats (2014 season)", "Rapid Solicitors Stadium", "11,000", "Wakefield, West Yorkshire"], ["Hull (2014 season)", "Kingston Communications Stadium", "25,404", "Kingston upon Hull, East Riding of Yorkshire"], ["Huddersfield Giants (2014 season)", "John Smith's Stadium", "24,544", "Huddersfield, West Yorkshire"], ["Castleford Tigers (2014 season)", "The Wish Communications Stadium", "11,750", "Castleford, West Yorkshire"], ["St Helens RLFC (2014 season)", "Langtree Park", "18,000", "St Helens, Merseyside"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the next team listed after widnes vikings?
|
Wigan Warriors
|
Answer:
| 128
|
Table InputTable: [["Date", "Festival", "Location", "Awards", "Link"], ["Oct 9", "London Int. Festival of Science Fiction Film", "London, England\\n UK", "Closing Night Film", "Sci-Fi London"], ["Oct 9, Oct 11", "Sitges Film Festival", "Sitges, Catalonia\\n Spain", "", "Sitges Festival"], ["Sep 19", "Lund International Fantastic Film Festival", "Lund, Skåne\\n Sweden", "", "fff.se"], ["Sep 28", "Fantastic Fest", "Austin, Texas\\n USA", "", "FantasticFest.com"], ["Feb 2–5, Feb 11", "Santa Barbara International Film Festival", "Santa Barbara, California USA", "Top 11 \"Best of the Fest\" Selection", "sbiff.org"], ["May 21–22, Jun 11", "Seattle International Film Festival", "Seattle, Washington USA", "", "siff.net"], ["Sep 16", "Athens International Film Festival", "Athens, Attica\\n Greece", "Best Director", "aiff.gr"], ["Nov 12, Nov 18", "Indonesia Fantastic Film Festival", "Jakarta, Bandung\\n Indonesia", "", "inaff.com"], ["Nov 16–18", "AFF", "Wrocław, Lower Silesia\\n Poland", "", "AFF Poland"], ["Jul 18, Jul 25", "Fantasia Festival", "Montreal, Quebec Canada", "Special Mention\\n\"for the resourcefulness and unwavering determination by a director to realize his unique vision\"", "FanTasia"], ["Oct 1, Oct 15", "Gwacheon International SF Festival", "Gwacheon, Gyeonggi-do\\n South Korea", "", "gisf.org"], ["Nov 11", "Les Utopiales", "Nantes, Pays de la Loire\\n France", "", "utopiales.org"], ["Oct 23", "Toronto After Dark", "Toronto, Ontario\\n Canada", "Best Special Effects\\nBest Musical Score", "torontoafterdark.com"], ["Oct 17, Oct 20", "Icon TLV", "Tel Aviv, Central\\n Israel", "", "icon.org.il"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many festivals was the film shown at?
|
14
|
Answer:
| 128
|
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["10", "8", "Tim Schenken", "Brabham-Ford", "76", "+ 4 Laps", "18", ""], ["8", "27", "Henri Pescarolo", "March-Ford", "77", "+ 3 Laps", "13", ""], ["7", "22", "John Surtees", "Surtees-Ford", "79", "+ 1 Lap", "10", ""], ["6", "24", "Rolf Stommelen", "Surtees-Ford", "79", "+ 1 Lap", "16", "1"], ["5", "1", "Emerson Fittipaldi", "Lotus-Ford", "79", "+ 1 Lap", "17", "2"], ["4", "9", "Denny Hulme", "McLaren-Ford", "80", "+ 1:06.7", "8", "3"], ["9", "15", "Pedro Rodríguez", "BRM", "76", "+ 4 Laps", "5", ""], ["Ret", "7", "Graham Hill", "Brabham-Ford", "1", "Accident", "9", ""], ["Ret", "10", "Peter Gethin", "McLaren-Ford", "22", "Accident", "14", ""], ["1", "11", "Jackie Stewart", "Tyrrell-Ford", "80", "1:52:21.3", "1", "9"], ["DNQ", "6", "Mario Andretti", "Ferrari", "", "", "", ""], ["3", "4", "Jacky Ickx", "Ferrari", "80", "+ 53.3", "2", "4"], ["Ret", "2", "Reine Wisell", "Lotus-Ford", "21", "Wheel bearing", "12", ""], ["Ret", "5", "Clay Regazzoni", "Ferrari", "24", "Accident", "11", ""], ["2", "17", "Ronnie Peterson", "March-Ford", "80", "+ 25.6", "6", "6"], ["Ret", "12", "François Cevert", "Tyrrell-Ford", "5", "Accident", "15", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers completed 80 laps?
|
4
|
Answer:
| 128
|
Table InputTable: [["Period", "Live births per year", "Deaths per year", "Natural change per year", "CBR*", "CDR*", "NC*", "TFR*", "IMR*"], ["1950-1955", "139 000", "66 000", "74 000", "52.6", "24.8", "27.8", "6.86", "174"], ["1990-1995", "471 000", "192 000", "279 000", "55.5", "22.7", "32.8", "7.78", "146"], ["1965-1970", "229 000", "105 000", "124 000", "56.2", "25.8", "30.4", "7.32", "164"], ["1960-1965", "195 000", "89 000", "105 000", "55.5", "25.5", "30.1", "7.13", "167"], ["1970-1975", "263 000", "121 000", "142 000", "55.8", "25.6", "30.2", "7.52", "162"], ["1955-1960", "164 000", "76 000", "88 000", "53.8", "24.9", "29.0", "6.96", "171"], ["2005-2010", "705 000", "196 000", "509 000", "49.5", "13.8", "35.7", "7.19", "96"], ["1975-1980", "301 000", "138 000", "164 000", "55.1", "25.1", "29.9", "7.63", "161"], ["1980-1985", "350 000", "157 000", "193 000", "55.4", "24.8", "30.6", "7.76", "159"], ["1985-1990", "406 000", "179 000", "227 000", "55.9", "24.6", "31.3", "7.81", "155"], ["2000-2005", "614 000", "194 000", "420 000", "51.3", "16.2", "35.1", "7.40", "113"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the first interval of five years to have more than 100,000 deaths?
|
1965-1970
|
Answer:
| 128
|
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Runner-up", "1.", "25 October 2009", "Kremlin Cup, Russia", "Hard (i)", "Mikhail Youzhny", "7–6(7–5), 0–6, 4–6"], ["Winner", "2.", "23 October 2011", "Kremlin Cup, Russia", "Hard (i)", "Viktor Troicki", "6–4, 6–2"], ["Runner-up", "5.", "30 October 2011", "St. Petersburg Open, Russia", "Hard (i)", "Marin Čilić", "3–6, 6–3, 2–6"], ["Runner-up", "2.", "19 June 2010", "UNICEF Open, Netherlands", "Grass", "Sergiy Stakhovsky", "3–6, 0–6"], ["Runner-up", "7.", "22 July 2012", "Swiss Open, Switzerland", "Clay", "Thomaz Bellucci", "7–6(8–6), 4–6, 2–6"], ["Winner", "3.", "15 July 2012", "Stuttgart Open, Germany", "Clay", "Juan Mónaco", "6–4, 5–7, 6–3"], ["Runner-up", "4.", "18 June 2011", "Aegon International, United Kingdom", "Grass", "Andreas Seppi", "6–7(5–7), 6–3, 3–5 ret."], ["Runner-up", "6.", "8 January 2012", "Chennai Open, India", "Hard", "Milos Raonic", "7–6(7–4), 6–7(4–7), 6–7(4–7)"], ["Winner", "1.", "2 October 2011", "Malaysian Open, Malaysia", "Hard (i)", "Marcos Baghdatis", "6–4, 7–5"], ["Winner", "4.", "6 January 2013", "Chennai Open, India", "Hard", "Roberto Bautista-Agut", "3–6, 6–1, 6–3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:kremlin cup and st petersburg open are in what country?
|
Russia
|
Answer:
| 128
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "Australia (AUS)", "2", "1", "0", "3"], ["5", "Switzerland (SUI)", "0", "2", "1", "3"], ["2", "Italy (ITA)", "1", "1", "1", "3"], ["3", "Germany (EUA)", "1", "0", "1", "2"], ["7", "France (FRA)", "0", "0", "1", "1"], ["7", "Great Britain (GBR)", "0", "0", "1", "1"], ["4", "Soviet Union (URS)", "1", "0", "0", "1"], ["6", "United States (USA)", "0", "1", "0", "1"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many gold medals did australia and switzerland total?
|
2
|
Answer:
| 128
|
Table InputTable: [["Thread\\nnominal size", "Outer diameter\\n[mm (in)]", "Threads per inch\\n(TPI)", "Pitch\\n[in (mm)]", "Inner diameter\\n[mm (in)]", "Cable diameter\\n[mm (in)]"], ["PG42", "54.0 (2.126)", "16", "0.0625 (1.5875)", "52.48 (2.066)", ""], ["PG48", "59.3 (2.335)", "16", "0.0625 (1.5875)", "57.78 (2.275)", ""], ["PG36", "47.0 (1.850)", "16", "0.0625 (1.5875)", "45.48 (1.791)", ""], ["PG29", "37.0 (1.457)", "16", "0.0625 (1.5875)", "35.48 (1.397)", "18 to 25 (0.709 to 0.984)"], ["PG11", "18.6 (0.732)", "18", "0.05556 (1.4112)", "17.26 (0.680)", "5 to 10 (0.197 to 0.394)"], ["PG7", "12.5 (0.492)", "20", "0.05 (1.270)", "11.28 (0.444)", "3 to 6.5 (0.118 to 0.256)"], ["PG9", "15.5 (0.610)", "18", "0.05556 (1.4112)", "13.86 (0.546)", "4 to 8 (0.157 to 0.315)"], ["PG16", "22.5 (0.886)", "18", "0.05556 (1.4112)", "21.16 (0.833)", "10 to 14 (0.394 to 0.551)"], ["PG13.5", "20.4 (0.803)", "18", "0.05556 (1.4112)", "19.06 (0.750)", "6 to 12 (0.236 to 0.472)"], ["PG21", "28.3 (1.114)", "16", "0.0625 (1.5875)", "26.78 (1.054)", "13 to 18 (0.512 to 0.709)"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of sizes that has an inner diameter above 50 mm?
|
2
|
Answer:
| 128
|
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["5", "July 8", "Watkins Glen‡", "Hal Shaw, Jr.\\n Monte Shelton", "Porsche 935", "Brian Fuerstenau\\n Bob Tullius", "Jaguar XJS"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["3", "June 11", "Portland", "Tuck Thomas", "Chevrolet Monza", "Bob Matkowitch", "Chevrolet Corvette"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country has the larger number of circuits?
|
USA
|
Answer:
| 128
|
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1.", "Brazil", "21", "9", "12", "42"], ["9.", "Argentina", "0", "2", "0", "2"], ["2.", "United States", "9", "3", "6", "18"], ["8.", "Russia", "0", "2", "3", "5"], ["3.", "China", "1", "9", "8", "18"], ["7.", "Germany", "0", "5", "1", "6"], ["10.", "Switzerland", "0", "1", "1", "2"], ["4.", "Australia", "1", "1", "1", "3"], ["6.", "Estonia", "1", "0", "0", "1"], ["12.", "Austria", "0", "0", "1", "1"], ["4.", "Netherlands", "1", "1", "1", "3"], ["11.", "Norway", "0", "1", "0", "1"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did brazil and the united states have the highest gold count?
|
Yes
|
Answer:
| 128
|
Table InputTable: [["Year", "Car", "Start", "Qual", "Rank", "Finish", "Laps", "Led", "Retired"], ["1929", "23", "11", "112.146", "15", "17", "91", "0", "Supercharger"], ["1928", "8", "4", "117.031", "4", "10", "200", "33", "Running"], ["1927", "27", "27", "107.765", "22", "3", "200", "0", "Running"], ["1933", "34", "12", "113.578", "15", "7", "200", "0", "Running"], ["1939", "62", "27", "121.749", "24", "11", "200", "0", "Running"], ["1937", "38", "7", "118.788", "16", "8", "200", "0", "Running"], ["1930", "9", "20", "100.033", "18", "20", "79", "0", "Valve"], ["1938", "17", "4", "122.499", "6", "17", "130", "0", "Rod"], ["1931", "37", "19", "111.725", "6", "18", "167", "0", "Crash T4"], ["1934", "8", "7", "113.733", "13", "17", "94", "0", "Rod"], ["1935", "44", "6", "115.459", "11", "21", "102", "0", "Magneto"], ["1932", "25", "20", "108.896", "34", "13", "184", "0", "Flagged"], ["1926", "31", "12", "102.789", "13", "11", "142", "0", "Flagged"], ["Totals", "Totals", "Totals", "Totals", "Totals", "Totals", "1989", "33", ""]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in what year did he lead the most laps in?
|
1928
|
Answer:
| 128
|
Table InputTable: [["Date", "Team", "Competition", "Round", "Leg", "Opponent", "Location", "Score"], ["October 4", "Standard Liège", "UEFA Cup", "Round 1", "Leg 2, Home", "Zenit St. Petersburg", "Stade Maurice Dufrasne, Liège", "1-1"], ["October 4", "Club Brugge", "UEFA Cup", "Round 1", "Leg 2, Home", "Brann", "Jan Breydel Stadium, Bruges", "1-2"], ["October 4", "Anderlecht", "UEFA Cup", "Round 1", "Leg 2, Away", "Rapid Wien", "Gerhard Hanappi Stadium, Vienna", "1-0"], ["October 25", "Anderlecht", "UEFA Cup", "Group Stage", "Match 1, Home", "Hapoel Tel Aviv", "Constant Vanden Stock Stadium, Anderlecht", "2-0"], ["September 20", "Club Brugge", "UEFA Cup", "Round 1", "Leg 1, Away", "Brann", "Brann Stadion, Bergen", "1-0"], ["August 30", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 2, Home", "Käerjeng", "Stade Maurice Dufrasne, Liège", "1-0"], ["August 15", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 1, Away", "Fenerbahçe", "Şükrü Saracoğlu Stadium, Istanbul", "0-1"], ["August 16", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 1, Away", "Käerjeng", "Stade Josy Barthel, Luxembourg", "3-0"], ["August 29", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 2, Home", "Fenerbahçe", "Constant Vanden Stock Stadium, Anderlecht", "0-2"], ["September 20", "Standard Liège", "UEFA Cup", "Round 1", "Leg 1, Away", "Zenit St. Petersburg", "Petrovsky Stadium, Saint Petersburg", "0-3"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many games were played after october 1st?
|
11
|
Answer:
| 128
|
Table InputTable: [["Golfer", "Country", "Wins", "Match Play", "Championship", "Invitational", "Champions"], ["Tiger Woods", "United States", "18", "3: 2003, 2004, 2008", "7: 1999, 2002, 2003,\\n2005, 2006, 2007, 2013", "8: 1999, 2000, 2001, 2005,\\n2006, 2007, 2009, 2013", "—"], ["Phil Mickelson", "United States", "2", "—", "1: 2009", "—", "1: 2009"], ["Hunter Mahan", "United States", "2", "1: 2012", "—", "1: 2010", "—"], ["Ernie Els", "South Africa", "2", "—", "2: 2004, 2010", "—", "—"], ["Geoff Ogilvy", "Australia", "3", "2: 2006, 2009", "1: 2008", "—", "—"], ["Ian Poulter", "England", "2", "1: 2010", "—", "—", "1: 2012"], ["Darren Clarke", "Northern Ireland", "2", "1: 2000", "—", "1: 2003", "—"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of wins listed for the united states?
|
22
|
Answer:
| 128
|
Table InputTable: [["Rank", "Country", "Box Office", "Year", "Box office\\nfrom national films"], ["12", "Brazil", "$0.72 billion", "2013", "17% (2013)"], ["11", "Italy", "$0.84 billion", "2013", "30% (2013)"], ["8", "Germany", "$1.3 billion", "2012", "–"], ["9", "Russia", "$1.2 billion", "2012", "–"], ["5", "France", "$1.7 billion", "2012", "33.3% (2013)"], ["2", "China", "$3.6 billion", "2013", "59% (2013)"], ["10", "Australia", "$1.2 billion", "2012", "4.1% (2011)"], ["-", "World", "$34.7 billion", "2012", "–"], ["7", "India", "$1.4 billion", "2012", "–"], ["3", "Japan", "$1.88 billion", "2013", "61% (2013)"], ["4", "United Kingdom", "$1.7 billion", "2012", "36.1% (2011)"], ["6", "South Korea", "$1.47 billion", "2013", "59.7% (2013)"], ["1", "Canada/United States", "$10.8 billion", "2012", "–"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:if italy and brazil combined box office revenues, what would be their new total?
|
$1.56 billion
|
Answer:
| 128
|
Table InputTable: [["Restaurant", "Location", "Date Opened", "Date Closed"], ["Verre at the Hilton Dubai Creek", "Dubai, United Arab Emirates", "", "October 2011"], ["Maze by Gordon Ramsay", "The Pearl-Qatar, Doha, Qatar", "2010", "March 2012"], ["Maze / Maze Grill by Gordon Ramsay", "Crown Metropol, Melbourne, Australia", "March 2010", "August 2011"], ["Gordon Ramsay at Conrad Tokyo", "Conrad Tokyo, Tokyo, Japan", "", "-"], ["Cerise by Gordon Ramsay", "Minato, Tokyo, Japan", "", "-"], ["Maze by Gordon Ramsay", "One and Only Hotel, Cape Town, South Africa", "April 2009", "July 2010"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when did the restaurant "verre" at the hilton dubai creek close?
|
October 2011
|
Answer:
| 128
|
Table InputTable: [["Position", "Driver", "No.", "Car", "Entrant", "Lak.", "Ora.", "San.", "Phi.", "Total"], ["19", "Chris Donnelly", "", "", "", "12", "-", "-", "-", "12"], ["", "Paul Barrett", "", "", "", "-", "-", "-", "12", "12"], ["21", "Brett Francis", "", "", "", "11", "-", "-", "-", "11"], ["", "Craig Wildridge", "", "", "", "-", "10", "-", "-", "10"], ["6", "Danny Osborne", "", "Mazda RX-7", "", "26", "10", "30", "-", "66'"], ["", "Ron O'Brien", "", "", "", "-", "-", "-", "10", "10"], ["17", "Phil Crompton", "49", "Ford EA Falcon", "Phil Crompton", "17", "-", "-", "-", "17"], ["5", "Bob Jolly", "3", "Holden VS Commodore", "Bob Jolly", "-", "28", "16", "32", "76"], ["8", "Mark Trenoweth", "", "Jaguar", "", "33", "24", "-", "-", "57"], ["15", "Gary Rowe", "47", "Nissan Stanza", "Gary Rowe", "-", "-", "21", "-", "21"], ["", "Domenic Beninca", "", "", "", "-", "-", "-", "21", "21"], ["22", "Shane Eklund", "", "", "", "10", "-", "-", "-", "10"], ["3", "James Phillip", "55", "Honda Prelude Chevrolet", "James Phillip", "26", "28", "28", "30", "112"], ["2", "Kerry Baily", "18", "Toyota Supra Chevrolet", "Kerry Baily", "38", "38", "36", "38", "150"], ["1", "John Briggs", "9", "Honda Prelude Chevrolet", "John Briggs", "42", "42", "42", "42", "168"], ["4", "Mick Monterosso", "2", "Ford Escort RS2000", "Mick Monterosso", "-", "34", "36", "34", "104"], ["11", "Kevin Clark", "116", "Ford Mustang GT", "Kevin Clark", "-", "-", "23", "23", "46"], ["18", "Allan McCarthy", "", "Alfa Romeo Alfetta", "", "14", "-", "-", "-", "14"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who finished immediately after danny osborne?
|
Mike Imrie
|
Answer:
| 128
|
Table InputTable: [["District", "Location", "Communities served"], ["Saint Anselm School", "Chester Township, Ohio", "Roman Catholic Diocese of Cleveland K - 8th grade; preschool"], ["Saint Helen's School", "Newbury, Ohio", "Roman Catholic Diocese of Cleveland K - 8th grade; parishioners and non-parishioners"], ["Notre Dame-Cathedral Latin", "Munson Township, Ohio", "Roman Catholic Diocese of Cleveland: open to 8th grade students who have attended a Catholic elementary school and others who have not"], ["Saint Mary's School", "Chardon, Ohio", "Roman Catholic Diocese of Cleveland preschool - 8th grade; parishioners and non-parishioners"], ["Solon/Bainbridge Montessori School of Languages", "Bainbridge Township, Ohio", "nonsectarian Montessori School: quarterly enrollment periods"], ["Hawken School", "Gates Mills, Ohio", "College preparatory day school: online application, site visit and testing"], ["Hershey Montessori Farm School", "Huntsburg Township, Ohio", "parent-owned, and chartered by Ohio Department of Education: application deadline January each year"], ["Agape Christian Academy", "Burton Township, Ohio and Troy Township, Ohio", "Accepts applications prior to the start of each school year"]]
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where is saint anslem school located?
|
Chester Township, Ohio
|
Answer:
| 128
|
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