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You are given a sentence in Spanish. Your job is to translate the Spanish sentence into English.
--------
Question: Y nos enfrentamos a increíbles retos en seguridad pública porque tenemos una situación en la que 2 / 3 de las personas en las cárceles están aún esperado juicio.
Answer: And we face unbelievable public safety challenges because we have a situation in which two thirds of the people in our jails are there waiting for trial.
Question: Pero no sabemos cuan rápido debemos recortarlas.
Answer: But we don't really know how quickly we have to cut them.
Question: Colores sin pigmentos: este pavo real crea colores con la forma.
Answer:
|
Color without pigments: this peacock is creating color with shape.
| 7
|
NIv2
|
task1226_ted_translation_es_en
|
fs_opt
|
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] |
TASK DEFINITION: Given a trivia question, classify broad topical category from this list: 'theater', 'geology', 'book', 'tv', 'astronomy', 'aviation', 'military', 'government', 'boxing', 'projects', 'metropolitan_transit', 'law', 'venture_capital', 'broadcast', 'biology', 'people', 'influence', 'baseball', 'spaceflight', 'media_common', 'cvg', 'opera', 'olympics', 'chemistry', 'visual_art', 'conferences', 'sports', 'language', 'travel', 'location', 'award', 'dining', 'martial_arts', 'comic_strips', 'computer', 'user', 'tennis', 'music', 'organization', 'food', 'event', 'transportation', 'fictional_universe', 'measurement_unit', 'meteorology', 'distilled_spirits', 'symbols', 'architecture', 'freebase', 'internet', 'fashion', 'boats', 'cricket', 'film', 'medicine', 'finance', 'comic_books', 'celebrities', 'soccer', 'games', 'time', 'geography', 'interests', 'common', 'base', 'business', 'periodicals', 'royalty', 'education', 'type', 'religion', 'automotive', 'exhibitions'.
PROBLEM: Boston lies in which state of the USA?
SOLUTION: location
PROBLEM: Charles Sands (USA), Margaret Abbot (USA) and George Lyon (Canada) were winners in what Olympic sport at the 1900 and 1904 games?
SOLUTION: sports
PROBLEM: What heavy metal band has a one-armed drummer?
SOLUTION:
|
music
| 8
|
NIv2
|
task900_freebase_qa_category_classification
|
fs_opt
|
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Given the task definition, example input & output, solve the new input case.
You will be given two pieces of text with the same meaning. One of them is simpler and easier to understand for non-native English speakers. Complex texts may contain more difficult words, have unnecessary phrases or contain long sentences. Your task is to choose the simpler piece of text. You are expected to output 'Text one' if the first sentence is simpler. Otherwise output 'Text two'.
Example: Text one: From its inception, it was designated a duty-free port and vied with the neighboring Sultanate of Pattani for trade
Text two: From the start, it was chosen to be a duty-free port to compete with the neighboring Sultanate of Pattani for trade.
Output: Text two
Text two has simpler words, ,so it is easier to understand by non-native English speakers.
New input case for you: Text one: It grows to up to 20 m, although it is typically more stunted in its native environment.
Text two: It grows to 20 m, and it is typically more stunted in its native environment.
Output:
|
Text two
| 1
|
NIv2
|
task112_asset_simple_sentence_identification
|
fs_opt
|
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] |
You are provided with an "Event" and it's "Intent" related to PersonX. Determine the sentiment value of the given input as either "Positive", "Negative", and "Unknown".
Let me give you an example: Event:PersonX treats PersonY's ___ well. Intent: 1) to leave a good impression over person y by doing everything perfectly well
The answer to this example can be: Positive
Here is why: In the input PersonX treats PersonY's in a good way. He fells calm and pleased by the work he has done. This refers to a "Positive" reaction.
OK. solve this:
Event:PersonX falls between the cracks. Intent:
Answer:
|
Unknown
| 8
|
NIv2
|
task923_event2mind_classifier
|
fs_opt
|
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] |
Q: Two analogies that relate objects to the associated rooms is given in the form "A : B. C : ?". "A : B" relates object A to room B. Your task is to replace the question mark (?) with the appropriate room for the given object C, following the "A : B" relation.
couch : parlor. refrigerator : ?
A:
|
kitchen
| 7
|
NIv2
|
task1157_bard_analogical_reasoning_rooms_for_containers
|
zs_opt
|
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-0.5223453044891357,
-0.35886484384536743,
0.04908043146133423,
0.48363012075424194,
0.3316996395587921,
0.4243123531341553,
-0.825300931930542,
0.22492477297782898,
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] |
In this task, you are given triplets. Each triplet is in the form of [subject, predicate, object]. Your task is to generate proper sentence that utilizes these triples. The objective is to construct a sentence that (a) captures the facts specified in the triples and (b) is a well-formed sentence easily understandable by a human. All triple values need not be used directly in the sentence as long as the facts are adequately captured.
Q: [['United States', 'LEADER_TITLE', 'President of the United States'], ['United States', 'LEADER_NAME', 'John Roberts'], ['United States', 'LEADER_NAME', 'Paul Ryan'], ['250 Delaware Avenue', 'LOCATION', 'United States']]
A: In the United States where the leader is known as the President of the United States, John Roberts is the Chief Justice, one of the leaders is Paul Ryan and it is where 200 Delaware Avenue is located.
****
Q: [['RCD Mallorca', 'GOALS_AGAINST', '34'], ['RCD Mallorca', 'GOAL_DIFFERENCE', '+23'], ['RCD Mallorca', 'GOALS_FOR', '57']]
A: The team scored 57 goals for themselves and had 34 goals scored against them, bring their goal difference to +23.
****
Q: [['10', 'WINNING_SCORE', '71-66-70-67=274'], ['10', 'MARGIN_OF_VICTORY', '3 strokes'], ['10', 'TOURNAMENT', 'BMW Asian Open 1'], ['[TABLECONTEXT]', '[TITLE]', 'Miguel Ángel Jiménez European Tour wins'], ['[TABLECONTEXT]', 'NUMBER', '10']]
A:
|
Miguel Ángel Jiménez won the bmw asian open 1 with a margin of victory of 2 strokes and a winning score of 274.
****
| 4
|
NIv2
|
task1409_dart_text_generation
|
fs_opt
|
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Classify the relation of question with context to one of these categories: 1) award received, 2) based on, collection, 3) conflict, 4) constellation, 5) convicted of, 6) date of death, 7) director, 8) drafted by, 9) educated at, 10) medical condition, 11) military branch, 12) narrative location, 13) occupation, 14) original network, 15) parent company, 16) point in time, 17) production company, 18) residence, 19) series, 20) service entry, 21) sex or gender, 22) spouse, 23) standards body question.
Ex Input:
Context : Warren McGlone (born September 17, 1969, in Philadelphia, Pennsylvania), known by the stage name Steady B, is an American hip hop emcee who, along with Schoolly D, the Fresh Prince, and Three Times Dope, was one of the first wave of Philadelphia-area emcees to gain notoriety in the mid to late 1980s.
Question : Which crime led to the conviction of Steady B?
Ex Output:
convicted of
Ex Input:
Context : According to Nielsen Media Research, ``Leslie's House'' was seen by 4.35 million viewers, a slight drop from the previous episode, ``The Set Up''.
Question : To which series does Leslie's House belong?
Ex Output:
series
Ex Input:
Context : Chris Krause later played collegiate football at Vanderbilt University, where he was a linebacker and nose guard.
Question : What college did Chris Krause go to?
Ex Output:
|
educated at
| 1
|
NIv2
|
task1328_qa_zre_relation_generation_from_question
|
fs_opt
|
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] |
Given an entity as input, output another entity which is part of the input entity. These are entities of meronym. In linguistics, meronymy is a semantic relation between a meronym denoting a part and a holonym denoting a whole. In simpler terms, a meronym (i.e., output entity) is in a part-of relationship with its holonym (i.e., input entity).
Q: cicatrix
A:
|
vesicle
| 4
|
NIv2
|
task471_haspart_answer_generation
|
zs_opt
|
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] |
Teacher:In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
Teacher: Now, understand the problem? Solve this instance: [-94, 87]
Student:
|
[181]
| 6
|
NIv2
|
task125_conala_pair_differences
|
zs_opt
|
[
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] |
Q: In this task you are given a tweet that contains some form of irony. You must classify the type of irony the tweet has. Label the tweets ("polarity","situational","other") based on the irony they have. Situational irony happens when a situation fails to meet some expectations, Label these instances as "situational". polarity irony happens when irony is achieved by inverting the intended sentence, Label these instances as "polarity". There are other kinds of ironies that are neither polarity nor situational, Label these instances as "other". Note that URLs in the text have been replaced with [Link].
Too late, thrown the #PS4 out of the window last night cus i couldn't play [Link]
A:
|
other
| 7
|
NIv2
|
task387_semeval_2018_task3_irony_classification
|
zs_opt
|
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] |
In this task, you will be shown a conversation and a question. You need to answer the question and choose the correct option based on the conversation. "W" and "M" in the conversations stand for "woman" and "man".
[EX Q]: M: If you'd like to go there for dinner this evening, I'll phone the restaurant. W: Thank you, but I promised my sister I'd take her to the airport., Question: What is the woman going to do this evening? (A) Go to dinner. (B) Visit her sister. (C) Go to the airport.
[EX A]: (C) Go to the airport.
[EX Q]: W: Hey, do you want to go for a picnic in the park tomorrow afternoon? M: I can't. I just started coaching a boys' football team. We have a game tomorrow. W: Oh, that sounds fun. Maybe I can come see it. M: Sure! The game starts at two, but we'll be there at 1:00 to prepare. It'll be at the football field beside the high school, across from the post office. W: OK, great. I'll be there at 1:30, then. But why did you decide to coach a football team? M: Well, I thought it might be a bad idea at first, because I was so busy at work. But then I thought, why not?, Question: When did the woman promise to arrive? (A) At 1:00. (B) At 1:30. (C) At 2:00.
[EX A]: (B) At 1:30.
[EX Q]: M: Hello, 6632278. W: Hi, Jack. It's me, Ann. I wasn't at school today. Have we got any homework to do for tomorrow? M: Let me see. Well, we've got to do the math problems on Page 40 in our textbook. W: All right. I've got it. M: Then, we have to go on with our reading for English. The history teacher wants us to read the chapter on the History of London for tomorrow, and write down the most important dates and events in that chapter. W: Anything else? Ah...ah, music? M: No, we haven't any music homework, but the science teacher is giving us a test on Friday, so we have to study for that. W: Oh no. I'm so bad at science. I hate it. Thanks, Jack. M: Don't mention it. See you tomorrow., Question: What test are the speakers going to take on Firday? (A) Science (B) History (C) Music
[EX A]:
|
(A) Science
| 6
|
NIv2
|
task247_dream_answer_generation
|
fs_opt
|
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] |
Teacher:You are given a sentence in Persian. Your job is to translate the Farsi sentence into Hebrew.
Teacher: Now, understand the problem? Solve this instance: امروزه این مساله نه تنها مشکل بزرگی برای ارتش به شمار میره ، بلکه مساله بزرگیه که در کلیه زمینه های پزشکی فراگیر شده. و اون اینه که ما چطور به جراحت نگاه می کنیم و چطور باید به سرعت اونها رو به روشی که روی بدن موثر باشد متوقف کنیم ؟
Student:
|
עכשיו, הבעיה הזו היא לא רק בעיה עצומה לצבא, אלא היא גם בעיה גדולה שנפוצה ברחבי השדה הרפואי. והיא איך אנחנו בעצם מסתכלים על פצעים ואיך אנחנו עוצרים אותם מהר בדרך שיכולה לעבוד עם הגוף?
| 6
|
NIv2
|
task1269_ted_translation_fa_he
|
zs_opt
|
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Given the task definition and input, reply with output. Generate an appropriate single-sentence summary for the given text such that it includes the main topic of the text.
It was the first time in 10 years that more has been borrowed in January than collected through tax and other income. January is usually a key revenue-raising month as it is when taxpayers submit their self-assessment returns. Tax income fell by less than £1bn, but the government spent £19.7bn more than last year on measures such as furlough. Government borrowing for this financial year has now reached £270.6bn, which is £222bn more than a year ago, said the Office for National Statistics (ONS), which published the data. The independent Office for Budget Responsibility (OBR) has estimated that borrowing could reach £393.5bn by the end of the financial year in March. That would be the highest amount in any year since the Second World War. The borrowing figure was lower than expected but that "should not be interpreted as a signal that the economy is withstanding the third lockdown relatively well", said Samuel Tombs, chief UK economist at Pantheon Macroeconomics. "A sharp £2.1bn year-over-year decline in interest payments, and the vanishing of contributions to the EU's budget, which totalled £2.2bn in January 2020, helped," he pointed out. The increase in borrowing has led to a steep increase in the national debt, which now stands at £2.11 trillion. The UK's overall debt has now reached 97.6% of gross domestic product (GDP) - a level not seen since the early 1960s. The ONS warned that although the impact of the pandemic on the public finances is becoming clearer, "its effects are not fully captured" in the current data, and that its estimates of tax receipts and borrowing are "subject to greater than usual uncertainty". It is an almost unbroken rule - January is a time when the Treasury coffers fill and more is paid in than is spent. But for the first time since the financial crisis, the Government had to borrow money in January to make up the gap between what it spent and what it raised in taxes. This near £9bn deficit though was actually better than expectations of £25bn of January borrowing. Receipts from taxes on workers and businesses held up on last year. The borrowing was mainly about £8bn extra spending on things like vaccines, protective equipment and testing, and support for jobs and wages up £5bn on last January. Over the course of this financial year the public finances are heading for borrowing of around £350bn - less bad than forecasts closer to £400bn, but still a peacetime record. This is the backdrop to the chancellor's budget in a fortnight, where he vows to be open and honest with the public about this challenge, suggesting tax rises at some point. The immediate focus though will have to remain on supporting the economy, as it is cautiously reopened. Hospitality companies have been excused from paying business rates and home buyers have had a break from paying stamp duty since July. Both these factors meant a drop in revenue for the government. But alcohol duty has risen by a quarter and self-assessed income tax receipts were £1.4bn higher. Overall, tax income fell about 1% to £80.3bn. Some of the self-assessed income tax gain probably came from the government's policy of allowing some later payments that were due from July, the ONS noted. In the 10 months to January, self-assessed income tax receipts were £26.3bn, £2bn less than in the same period a year earlier. More than has been £46bn spent covering salaries as part of the furlough scheme, and tens of billions of pounds on guaranteeing loans to businesses. In all, the Government has launched more than 40 schemes across the UK to help households and businesses through the coronavirus crisis. Chancellor Rishi Sunak said: "Since the start of the pandemic we've invested over £280bn to protect jobs, businesses and livelihoods across the UK - this is the fiscally responsible thing to do and the best way to support sustainable public finances in the medium term." Tax rises, eventually? In his Budget on 3 March, "the Chancellor likely won't shy away from setting out plans for borrowing to remain very high in 2021/22, probably close to 10% of GDP," said Mr Tombs. He predicted that the chancellor will also be able to avoid setting out future tax rises for 2022 and beyond, if the OBR maintains its upbeat view on the amount of long-term scarring caused by the recent downturn. But he warned that upward pressure on spending will increase over the coming years as the population ages and the Conservatives invest more to "level up" the country. "As a result, big tax rises eventually will have to be announced, with 2022 likely to be the worst year," said Mr Tombs. The Budget will aim to secure the recovery, not to fix the public finances, the Institute for Fiscal Studies said earlier this week. That means substantial tax rises should not be part of the coming Budget, it said. "Rishi Sunak needs to strike a balance between continuing support for jobs and businesses harmed by lockdowns, and weaning the economy off blanket support which will impede necessary economic adjustment," said Paul Johnson, IFS director. "For now, Mr Sunak needs to focus on support and recovery. A reckoning in the form of big future tax rises is highly likely, but not as yet inevitable."
|
UK government borrowing hit £8.8bn last month, the highest January figure since records began in 1993, reflecting the cost of pandemic support measures.
| 5
|
NIv2
|
task1357_xlsum_summary_generation
|
zs_opt
|
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] |
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
Let me give you an example: ['hey', 'everybody', 'ivan', 'from', 'weights', 'and', 'biases', 'here', 'in', 'this', 'video', "i'd"]
The answer to this example can be: ['CASE_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'CASE_DIFF', 'UNKNOWN_TYPE_DIFF', 'CASE_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF']
Here is why: This sentence is a good example since the input stream is a grammatically incorrect statement and the output labels correctly classify the words that were incorrect.
OK. solve this:
['', 'in', 'the', "Lord's", 'house', 'Museum', 'in', 'The', 'Hague', "we're", 'looking', 'at', 'one', 'of', "Rembrandt's", 'most', 'famous', 'paintings', 'this', 'is', 'the', 'anatomy', 'lesson', 'of', 'dr.', 'taupe', 'this', 'is', 'a', 'typical', 'group', 'portrait', 'an', 'important', 'type', 'of', 'painting', 'in', 'the', 'Dutch', 'Republic', 'in', 'the', '17th', 'century', 'this', 'happens', 'to', 'be', 'the', 'guild', 'of', 'surgeons', 'and', 'regularly', 'they', 'would', 'Commission', 'a', 'group', 'portrait', 'to', 'hang', 'in', 'the', 'public', 'space', 'where', 'their', 'guild', 'would', 'meet', 'once', 'a', 'year', 'there', 'would', 'be', 'a', 'public', 'dissection', 'where', 'some', 'element', 'of', 'the', 'body', 'would', 'be', 'explicated', 'and', "that's", 'what', "we're", 'seeing', 'here', 'now', 'this', 'is', 'not']
Answer:
|
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'CASE_AND_PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
| 8
|
NIv2
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
fs_opt
|
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] |
In this task you are given a sentence pair from wikipedia that have high lexical overlap. If the sentences have the same meaning and are just paraphrases of each other label them as "Paraphrase" , if not label them as "Not paraphrase". The two sentences are seperated by a new line.
Q: The most important rivers of the district are the Willkanuta on the right border of the district and the Sallqa Mayu , one of its western tributaries .
The most important rivers of the district are the Willkanuta on the right border of the district and Sallqa Mayu , one of its western tributaries .
A:
|
Paraphrase
| 4
|
NIv2
|
task400_paws_paraphrase_classification
|
zs_opt
|
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] |
You will be given a definition of a task first, then some input of the task.
In this task, you need to remove all words of a given length in the sentence. The number of letters in a word determine its length, for example, the length of the word "apple" is 5.
Sentence: 'a somewhat blurry image a decorated fridge'. Remove all words of length '9' in the given sentence.
Output:
|
a somewhat blurry image a fridge
| 1
|
NIv2
|
task377_remove_words_of_given_length
|
zs_opt
|
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] |
In this task, you need to count the occurrences of the given word in the given sentence.
Q: Sentence: 'a flock of ducks swimming in a body of water'. Count the occurrences of the word 'of' in the given sentence.
A:
|
2
| 4
|
NIv2
|
task158_count_frequency_of_words
|
zs_opt
|
[
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0.26091861724853516,
0.11760067939758301,
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] |
In this task, you are given two natural language statements with similar wording. You must choose the statement that makes less sense based on common sense knowledge. A '
' separates the statements. Use "first" or "second" to indicate which sentence makes less sense.
Q: She wore a chandelier in the train.
She wore a dress in the train.
A:
|
first
| 4
|
NIv2
|
task291_semeval_2020_task4_commonsense_validation
|
zs_opt
|
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] |
You will be given a definition of a task first, then some input of the task.
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
find me " mexican " food
Output:
|
trovami cibo "mexican".
| 1
|
NIv2
|
task173_spl_translation_en_it
|
zs_opt
|
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] |
In this task, you are given a hypothesis and an update. The hypothesis sentence is a statement that speaks of a socially normative behavior. In other words, it is a generalizing statement about how we expect people to behave in society. The update provides additional contexts about the situation that might UNDERMINE or SUPPORT the generalization. An undermining context provides a situation that weakens the hypothesis. A supporting context provides a situation that strengthens the generalization. Your task is to output 'strengthener' or 'weakener' if the update supports or undermines the hypothesis, respectively
[EX Q]: Hypothesis: It's wrong to take your friend's beer.
Update: They haven't even had a sip yet.
[EX A]: strengthener
[EX Q]: Hypothesis: It's fine to choose not to pursue a relationship with someone, for any reason.
Update: you have told the person before to leave you alone
[EX A]: strengthener
[EX Q]: Hypothesis: It is okay to not want to be in a relationship.
Update: You are already married.
[EX A]:
|
weakener
| 6
|
NIv2
|
task937_defeasible_nli_social_classification
|
fs_opt
|
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In this task, you are given a hypothesis and an update. The hypothesis sentence is a statement that speaks of a socially normative behavior. In other words, it is a generalizing statement about how we expect people to behave in society. The update provides additional contexts about the situation that might UNDERMINE or SUPPORT the generalization. An undermining context provides a situation that weakens the hypothesis. A supporting context provides a situation that strengthens the generalization. Your task is to output 'strengthener' or 'weakener' if the update supports or undermines the hypothesis, respectively
Let me give you an example: Hypothesis: You should help your family with funeral expenses.
Update: They have asked you to chip in
The answer to this example can be: strengthener
Here is why: If your family has asked you to chip in for the funeral expenses, you should help them.
OK. solve this:
Hypothesis: Don't let a friend drag you down.
Update: You know they're on a bad road.
Answer:
|
strengthener
| 8
|
NIv2
|
task937_defeasible_nli_social_classification
|
fs_opt
|
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] |
You will be given a definition of a task first, then some input of the task.
In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
We report the experimental results for our two tasks in terms of the correct classification rate (CCR). For sentiment analysis, we have a three-class problem (positive, negative, and neutral), where the classes are mutually exclusive. The CCR, averaged for a set of tweets, is defined to be the number of correctly-predicted sentiments over the number of groundtruth sentiments in these tweets. For NER, we consider that each tweet may reference up to four candidates, i.e., targeted entities. The CCR, averaged for a set of tweets, is the number of correctly predicted entities (candidates) over the number of groundtruth entities (candidates) in this set.
Question: What measures are used for evaluation?
Output:
|
correct classification rate (CCR)
| 1
|
NIv2
|
task460_qasper_answer_generation
|
zs_opt
|
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] |
Teacher:In this task you will be given a list of strings and you need to concatenate them.
Teacher: Now, understand the problem? Solve this instance: ['v', 'was', 'H', 'involved', 'G']
Student:
|
vwasHinvolvedG
| 6
|
NIv2
|
task079_conala_concat_strings
|
zs_opt
|
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In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
--------
Question: Being madly in love with all the advances in minimally invasive medicine and technology I often tell my friends the stories of how interventional radiology (IR) changes lives. One of these unintended stories led to a much bigger audience of TED community and spread the word about IR far beyond the circle of my friends. As the TED slogan promised, participating in the event 1 made me realize that our ideas of better medicine are worth sharing. It also made me think that better communication with the public is possible, and it does not take genius. It takes a willingness to try. We know that IR with its broad procedural spectrum, safety of minimally invasive approach, lower requirement for anesthesia and hospitalization, and cost-effectiveness has a strong stand in the evolving universal healthcare practice model. But, as Goethe said, knowing is not enough; we must apply. 2 Then, how can we as medical community increase the exercise of IR procedures? The starting point is to accept that many people, including medical professionals, do not know what diseases we can treat and what diagnostic or therapeutic services we can provide. Either it is a palliative treatment of metastases, or elective embolization of uterine fibroids, or emergent lysis of pulmonary embolism-it is our responsibility to find the appropriate patients and let both patients and primary physicians know what options we have to offer.
Answer: Journal Pre-proof Guest Editorial: Radiology Nurses Can Raise the Impact on Promoting IR
Question: Purpose: Despite their controversial role, corticosteroids (CS) are frequently administered to patients with H1N1 virus infection with severe respiratory failure secondary to viral pneumonia. We hypothesized that invasive pulmonary aspergillosis (IPA) is a frequent complication in critically ill patients with H1N1 virus infection and that CS may contribute to this complication. Methods: We retrospectively selected all adult patients with confirmed H1N1 virus infection admitted to the intensive care unit (ICU) of two tertiary care hospitals from September 2009 to March 2011. Differences in baseline factors, risk factors, and outcome parameters were studied between patients with and without IPA. Results: Of 40 critically ill patients with confirmed H1N1, 9 (23 %) developed IPA 3 days after ICU admission. Five patients had proven and four had probable IPA. Significantly more IPA patients received CS within 7 days before ICU admission (78 versus 23 %, p = 0.002). IPA patients also received significantly higher doses of CS before ICU admission [hydrocortisone equivalent 800 (360-2,635) versus 0 (0-0) mg, p = 0.005]. On multivariate analysis, use of CS before ICU admission was independently associated with IPA [odds ratio (OR) 14.4 (2.0-101.6), p = 0.007]. Conclusions: IPA was diagnosed in 23 % of critically ill patients with H1N1 virus infection after a median of 3 days after ICU admission. Our data suggest that use of CS 7 days before ICU admission is an independent risk factor for fungal superinfection. These findings may have consequences for clinical practice as they point out the need for increased awareness of IPA, especially in those critically ill H1N1 patients already receiving CS.
Answer: Invasive pulmonary aspergillosis is a frequent complication of critically ill H1N1 patients: a retrospective study
Question: Codon usage bias (CUB) is an important evolutionary feature in a genome which provides important information for studying organism evolution, gene function and exogenous gene expression. The CUB and its shaping factors in the nuclear genomes of four sequenced cotton species, G. arboreum (A 2 ), G. raimondii (D 5 ), G. hirsutum (AD 1 ) and G. barbadense (AD 2 ) were analyzed in the present study. The effective number of codons (ENC) analysis showed the CUB was weak in these four species and the four subgenomes of the two tetraploids. Codon composition analysis revealed these four species preferred to use pyrimidinerich codons more frequently than purine-rich codons. Correlation analysis indicated that the base content at the third position of codons affect the degree of codon preference. PR2-bias plot and ENC-plot analyses revealed that the CUB patterns in these genomes and subgenomes were influenced by combined effects of translational selection, directional mutation and other factors. The translational selection (P2) analysis results, together with the non-significant correlation between GC12 and GC3, further revealed that translational selection played the dominant role over mutation pressure in the codon usage bias. Through relative synonymous codon usage (RSCU) analysis, we detected 25 high frequency codons preferred to end with T or A, and 31 low frequency codons inclined to end with C or G in these four species and four subgenomes. Finally, 19 to 26 optimal codons with 19 common ones were determined for each species and subgenomes, which preferred to end with A or T. We concluded that the codon usage bias was weak and the translation selection was the main shaping factor in nuclear genes of these four cotton genomes and four subgenomes. OPEN ACCESS Citation: Wang L, Xing H, Yuan Y, Wang X, Saeed M, Tao J, et al. (2018) Genome-wide analysis of codon usage bias in four sequenced cotton species. PLoS ONE 13(3): e0194372. https://doi. codon known as synonymous codons. The synonymous codons are not used at equal frequencies in coding sequences in many organisms [1]. This phenomenon called 'synonymous codon usage bias (SCUB)' reflects non-uniform usage of synonymous codons encoding the same amino acid during the translation of genes to proteins [2,3]. The degree of SCUB divergence varies greatly among different species and genes [4-7]. SCUB was affected by many factors, including directional mutation, neutral selection [8], GC content, synonymous substitution rate [9], tRNA abundance [10], selection for efficient translation initiation [11], codon hydropathy and DNA replication initiation site [12], gene length [13] and expression level [14] , etc. Of these factors, directional mutation and neutral selection are the two main ones, with varying relative importance in different species [15] [16][17]. The codon usage patterns always represent balance between the directional mutation and the neutral selection that leads to translational efficiency of genes [8] [9] [10] [11] . SCUB patterns were also associated with phylogenetic relationship among given species. Distant phylogenetic species usually has greater variations in codon usage bias [18,19]. Information on the SCUB patterns can provide significant insights pertaining to the prediction, classification, and molecular evolution of genes, design of highly expressed genes and cloning vectors and reveal about the host-pathogen coevolution and adaptation of pathogens to specific hosts [20,21]. Clustering results based on relative synonymous codon usage (RSCU) values could provide useful reference for phylogenetic relationship analysis [18,19,22]. Cotton (Gossypium spp.) is the main source of renewable textile fibers and is also grown to produce vegetable oil and high protein meals for humans and livestock [23]. The genus Gossypium includes around 46 diploid (2n = 2x = 26) and 6 tetraploid (2n = 4x = 52) and 1 purported species [24][25][26], including four commercial ones, G. arboreum (A 2 ), G. herbaceum (A 1 ), G. hirsutum (AD 1 ) and G. barbadense (AD 2 ). It has been proposed that all diploid cotton species may have evolved from a common ancestor and allopolyploid cotton may have appeared through hybridization and subsequent polyploidization events between the A-and D-subgenome progenitors. The D-genome species G. raimondii (D 5 ) and the A-genome species much like modern G. arboreum (A 2 ) and G. herbaceum (A 2 ) are the donor species for the D and A chromosome groups of the tetraploid cotton species, respectively [27][28]. Recently, the nuclear genome sequences of G. arboreum, G. raimondii, G. hirsutum and G. barbadense, and chloroplast and mitochondrial genome sequences of G. hirsutum have successively been released [29][30][31][32][33][34][35][36][37][38], which has advanced the understanding of cotton genomics and genetics, and made it possible to investigate SCUB patterns in cotton nuclear and organelle genomes. But until now, SCUB analysis has been performed only in chloroplast genome of G. hirsutum [36]. The purpose of this study was to analyze the SCUB patterns of the four sequenced cotton species and explore the key factors influencing codon choice.
Answer:
|
Genome-wide analysis of codon usage bias in four sequenced cotton species
| 7
|
NIv2
|
task1161_coda19_title_generation
|
fs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a stereotype or anti-stereotype. You are expected to classify the passage into three classes: stereotype, anti-stereotype, and unrelated.
Example: Passage: The game-winning football player is very aggressive.
Output: Stereotype
It is a stereotype because we have a standardized image that game-winning players are commonly aggresive. There is no mention of the football player's aggresive behavior.
New input case for you: Passage: Norway has many mythological stories. That country welcomes people from all over the world.
Output:
|
Anti-stereotype
| 1
|
NIv2
|
task279_stereoset_classification_stereotype
|
fs_opt
|
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] |
Detailed Instructions: Given a simple high-school level math question, you are required to solve it and provide the final answer. The final answer is always a single number. These questions can range from a variety of topics like simple arithmetic, solving equations, converting a quantity from one unit to another, finding remainders/GCD/LCM, finding probabilities etc. Each question has only one correct answer. This answer can be a positive or negative integer, a fraction or a decimal number. If the answer is a negative number use the hyphen (e.g. -42) symbol for the minus sign. For decimal numbers, do not add extra zeros after the decimal point. For fractional numbers, separate the numerator and denominator using a forward slash (e.g. 3/25).
Q: Two letters picked without replacement from {t: 1, r: 14}. What is prob of sequence rt?
A:
|
1/15
| 9
|
NIv2
|
task835_mathdataset_answer_generation
|
zs_opt
|
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] |
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that contradict each other. Your job is to alter sentence 2 so that the pair agree with each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Q: Sentence 1: A crowd of people who are demonstrating peacefully. Sentence 2: A crowd starts a riot after protesting the funeral of a famous celebrity.
A: There is a group demonstrating peacefully.
****
Q: Sentence 1: A young child drawing on a chalkboard. Sentence 2: The child is eating lunch.
A: The kid is writing on the chalkboard.
****
Q: Sentence 1: A dog jumping high to clear the bars. Sentence 2: The dog is sleeping.
A:
|
There is a dog outdoors
****
| 4
|
NIv2
|
task186_snli_contradiction_to_entailment_text_modification
|
fs_opt
|
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] |
Teacher: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Polish.
Teacher: Now, understand the problem? If you are still confused, see the following example:
♫ עם הכוח לעמוד ♫ ♫ בחצותה את הגבול ♫ ♫ היא אמרה, "" אתם תגדלו חופשיים על האדמה הזו "" ♫ ♫ נשים של תקווה ♫ ♫ נשים של שינוי ♫ ♫ נשים של מלחמה וכאב ♫ ♫ אני יכולה להרגיש את הכוח שלכן ♫ ♫ במילים אלו היא אמרה ♫ ♫ אם אתן מרגישות חסרות ישע ♫ ♫ עיזרו למישהו ♫ ♫ אם אתן מרגישות חסרות ישע ♫ ♫ עיזרו למישהו ♫ ♫ אף אחד לא באמת יודע ♫ ♫ כמה רחוק הן תלכנה ♫ ♫ כדי להשאר בחיים ♫ ♫ אף אחד לא באמת יודע ♫ ♫ כמה רחוק הן תלכנה ♫
Solution: życiu stawić czoła Granicę przekrocz "" Będziesz wolna "", już ktoś tam woła. Kobiety nadziei Kobiety zmian Kobiety wojny i bólu Czuję waszą siłę tak ona powiedziała Jeśli czujesz się bezsilna, pomóż komuś Jeśli czujesz się bezsilna pomóż komuś Nikt naprawdę nie wie jak daleko pójdą by dalej żyć Nikt naprawdę nie wie jak daleko pójdą
Reason: The Hebrew sentence is correctly translated into Polish, because the meaning is preserved.
Now, solve this instance: ואמרתי כבדיחה — כבדיחה, אמרתי, "" עשיתי את החשבון. לווריזון יש 70 מיליון לקוחות.
Student:
|
Postanowiłem, że opowiem taki dowcip: "" Policzmy: jeśli Verizon ma 70 milionów użytkowników,
| 2
|
NIv2
|
task1112_ted_translation_he_pl
|
fs_opt
|
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] |
In this task, you are given an input i,A where i is an integer and A is an array. You need to find every ith element of A starting with the 1st element.
Input: Consider Input: 1, ['e', 'u']
Output: e, u
Input: Consider Input: 5, ['721', 'O', 'W', 'N', 'v', 'D', 'B', '7371', '2311', '4289', 'U', '4843', '1089', 'z', '469', '7917', '811', '1929', '911', 'x', '5805', 'B', '2889', 'D', '8577', '5263', 'S', 'w', 'e', '2479', '7489', '4813', '9983', '2583', '8589', '287', '8719', 'l', '1135', 'w', '2525', 'm', 'i', '3721', 'x', '2105', '7935', '4845', '8367', '6349']
Output: 721, D, U, 7917, 5805, 5263, 7489, 287, 2525, 2105
Input: Consider Input: 4, ['8241', 'G', 'B', 'a', 'b', '7067', 'g', '8521', 'v', 'a', '5175', '455']
|
Output: 8241, b, v
| 2
|
NIv2
|
task1542_every_ith_element_from_starting
|
fs_opt
|
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] |
Part 1. Definition
This task is about generating an incorrect answer to a question given the question and a true statement related to the question. The answer must be related to the question, but incorrectly answer it given the context.
Part 2. Example
Fact: deep sea animals live deep in the ocean. Question: Frilled sharks and angler fish live far beneath the surface of the ocean, which is why they are known as?
Answer: Far Sea Animals
Explanation: This is an incorrect answer that is related to the question. This is a good output.
Part 3. Exercise
Fact: a beach ball contains gas. Question: In order to play with a beach ball, you need to fill it with?
Answer:
|
with ice
| 7
|
NIv2
|
task1400_obqa_incorrect_answer_generation
|
fs_opt
|
[
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] |
You are given a sentence in English. Your job is to translate the English sentence into Hebrew.
[EX Q]: And you see me worried and trying to protect my child, because you don't leave anyone with this kind of child, even a minister.
[EX A]: ואתם רואים שאני מודאג ומנסה להגן על הילדה שלי כי אסור להשאיר ילדה כזו בחברת מישהו, אפילו אם הוא שר.
[EX Q]: Anyway, in 1992, the Mujahideen took all Afghanistan.
[EX A]: בכל אופן, בשנת 1992, המוג 'אהדין כבשו את כל אפגניסטן.
[EX Q]: And we'll begin to be able to do as Cody does, and actually be in touch with these incredible models, these elders that have been here far, far longer than we have.
[EX A]:
|
ונתחיל להיות מסוגלים לעשות כמו שקודי עושה, ובאמת להיות בקשר עם המודלים המדהימים הללו, הקשישים שהיו כאן הרבה מאוד לפנינו.
| 6
|
NIv2
|
task1221_ted_translation_en_he
|
fs_opt
|
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] |
Detailed Instructions: In this task, you will be shown an English sentence. You need to classify the sentence as either a representation of an anaphor number agreement or as an incorrect representation. An anaphor is an expression whose interpretation depends upon another expression. Anaphor number agreement is a restriction where a phrase agrees with the preceeding expression: plurals match plurals or singular expressions match singular expressions. In this task a valid representation of anaphor number agreement should be denoted as 'good' while everything else should be denoted as 'bad'. A correct representation of an anaphor number agreement will be a grammatically correct instance of a sentence where the subject and self-referencing nouns match plurality. An incorrect representation is a sentence in which the subject and self-referencing noun's plurality do not match.
Q: That movie has disagreed with themselves.
A:
|
bad
| 9
|
NIv2
|
task1560_blimp_binary_classification
|
zs_opt
|
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] |
Q: In this task, you are given a sentence in English and your task is to translate it into Spanish. In translation, keep the numbers and capitalization (capitalize only the first word of each sentence and name).
This is understandable, because it is highly likely that Member States which start to cut back on state aid will cause companies to leave, with adverse effects on employment.
A:
|
Es comprensible, porque el Estado miembro que empiece reduciendo las ayudas estatales corre el riesgo de que las empresas se vayan, con las correspondientes consecuencias negativas para el empleo.
| 7
|
NIv2
|
task530_europarl_en_es_translation
|
zs_opt
|
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] |
Teacher: Given a set of five words, generate the word from the set that does not belong (i.e. is the least relevant) with the other words. Words are separated by commas.
Teacher: Now, understand the problem? If you are still confused, see the following example:
excavator, crane, pelican, hoist, upraise
Solution: pelican
Reason: The common category here are words related to construction. A pelican is not related to construction because it is a type of bird.
Now, solve this instance: ashamed, remorseful, loveful, down, ground
Student:
|
ground
| 2
|
NIv2
|
task142_odd-man-out_classification_no_category
|
fs_opt
|
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] |
In this task, you're expected to write answers to questions involving multiple references to the same entity. The answer to the question should be unambiguous and a phrase in the paragraph. Most questions can have only one correct answer.
--------
Question: Passage: Zappa expressed opinions on censorship when he appeared on CNN's Crossfire TV series and debated issues with Washington Times commentator John Lofton in 1986. On September 19, 1985, Zappa testified before the United States Senate Commerce, Technology, and Transportation committee, attacking the Parents Music Resource Center or PMRC, a music organization co-founded by Tipper Gore, wife of then-senator Al Gore. The PMRC consisted of many wives of politicians, including the wives of five members of the committee, and was founded to address the issue of song lyrics with sexual or satanic content. During Zappa's testimony, he stated that there was a clear conflict of interest between the PMRC due to the relations of its founders to the politicians who were then trying to pass what he referred to as the "Blank Tape Tax." Kandy Stroud, a spokeswoman for the PMRC, announced that Senator Gore (who co-founded the committee) was a co-sponsor of that legislation. Zappa suggested that record labels were trying to get the bill passed quickly through committees, one of which was chaired by Senator Strom Thurmond, who was also affiliated with the PMRC. Zappa further pointed out that this committee was being used as a distraction from that bill being passed, which would lead only to the benefit of a select few in the music industry.Zappa saw their activities as on a path towards censorship, and called their proposal for voluntary labelling of records with explicit content "extortion" of the music industry.In his prepared statement, he said:
The PMRC proposal is an ill-conceived piece of nonsense which fails to deliver any real benefits to children, infringes the civil liberties of people who are not children, and promises to keep the courts busy for years dealing with the interpretational and enforcemental problems inherent in the proposal's design. It is my understanding that, in law, First Amendment issues are decided with a preference for the least restrictive alternative. In this context, the PMRC's demands are the equivalent of treating dandruff by decapitation. ... The establishment of a rating system, voluntary or otherwise, opens the door to an endless parade of moral quality control programs based on things certain Christians do not like. What if the next bunch of Washington wives demands a large yellow "J" on all material written or performed by Jews, in order to save helpless children from exposure to concealed Zionist doctrine?Zappa set excerpts from the PMRC hearings to Synclavier music in his composition "Porn Wars" on the 1985 album Frank Zappa Meets the Mothers of Prevention, and the full recording was released in 2010 as Congress Shall Make No Law... Zappa is heard interacting with Senators Fritz Hollings, Slade Gorton and Al Gore.
Question: What is the first name of the person who saw the PMRC's activities as on a path towards censorship, and called their proposal for voluntary labelling of records with explicit content "extortion" of the music industry?
Answer: Frank.
Question: Passage: Music critic J. D. Considine noted "on albums, Jackson's sound isn't defined by her voice so much as by the way her voice is framed by the lush, propulsive production of Jimmy Jam and Terry Lewis." Wendy Robinson of PopMatters said "the power of Janet Jackson's voice does not lie in her pipes. She doesn't blow, she whispers ... Jackson's confectionary vocals are masterfully complemented by gentle harmonies and balanced out by pulsing rhythms, so she's never unpleasant to listen to."Matthew Perpetus of Fluxblog suggested Jackson's vocal techniques as a study for indie rock music, considering it to possess "a somewhat subliminal effect on the listener, guiding and emphasizing dynamic shifts without distracting attention from its primal hooks." Perpetus added: "Her voice effortlessly transitions from a rhythmic toughness to soulful emoting to a flirty softness without overselling any aspect of her performance ... a continuum of emotions and attitudes that add up to the impression that we're listening to the expression of a fully-formed human being with contradictions and complexities."Jackson's music has encompassed a broad range of genres. Her records from the 1980s have been described as being influenced by Prince, as her producers are ex-members of the Time. Sal Cinquemani wrote that in addition to defining Top 40 radio, she "gave Prince's Minneapolis sound a distinctly feminine—and, with songs like 'What Have You Done for Me Lately?,' 'Nasty,' 'Control,' and 'Let's Wait Awhile,' a distinctly feminist—spin."On Control, Richard J. Ripani documented that she, Jam and Lewis had "crafted a new sound that fuses the rhythmic elements of funk and disco, along with heavy doses of synthesizers, percussion, sound effects, and a rap music sensibility." Author Rickey Vincent stated that she has often been credited for redefining the standard of popular music with the industrial-strength beats of the album. She is considered a trendsetter in pop balladry, with Richard Rischar stating "the black pop ballad of the mid-1980s had been dominated by the vocal and production style that was smooth and polished, led by singers Whitney Houston, Janet Jackson, and James Ingram."Jackson continued her musical development by blending pop and urban music with elements of hip-hop in the nineties. This included a softer representation, articulated by lush, soulful ballads and up-tempo dance beats. She is described by music critic Greg Kot as "an artist who has reshaped the sound and image of rhythm and blues" within the first decade of her career. Critic Karla Peterson remarked that "she is a sharp dancer, an appealing performer, and as 'That's the Way Love Goes' proves—an ace pop-song writer." Selected material from the following decade has been viewed less favorably, as Sal Cinquemani comments "except for maybe R.E.M., no other former superstar act has been as prolific with such diminishing commercial and creative returns."Jackson has changed her lyrical focus over the years, becoming the subject of analysis in musicology, African American studies, and gender studies. David Ritz compared Jackson's musical style to Marvin Gaye's, stating, "like Marvin, autobiography seemed the sole source of her music. Her art, also like Marvin's, floated over a reservoir of secret pain." Much of her success has been attributed to "a series of powerful, metallic grooves; her chirpy, multi-tracked vocals; and a lyrical philosophy built on pride and self-knowledge." Ritz also stated, "The mystery is the low flame that burns around the perimeters of Janet Jackson's soul. The flame feeds off the most highly combustible elements: survival and ambition, caution and creativity, supreme confidence and dark fear."During the 1980s, her lyrics embodied self-actualization, feminist principles, and politically driven ideology. Gillian G. Gaar described Control as "an autobiographical tale about her life with her parents, her first marriage, and breaking free." Jessie Carney Smith wrote "with that album, she asserted her independence, individuality, and personal power. She challenged audiences to see her as a transformed person, from an ingénue to a grow-up, multi-talented celebrity." Referring to Rhythm Nation 1814 as an embodiment of hope, Timothy E. Scheurer wrote "It may remind some of Sly Stone prior to There's a Riot Going On and other African-American artists of the 1970s in its tacit assumption that the world imagined by Dr. King is still possible, that the American Dream is a dream for all people."On Janet, Jackson began focusing on sexual themes. Shayne Lee wrote that her music over the following decade "brand[ed] her as one of the most sexually stimulating vocalists of the 1990s." Lilly J. Goren observed "Jackson's evolution from politically aware musician to sexy diva marked the direction that society and the music industry were encouraging the dance-rock divas to pursue." The Washington Post declared Jackson's public image over the course of her career had shifted "from innocence to experience, inspiring such carnal albums as 1993's 'Janet' and 1997's 'The Velvet Rope', the latter of which explored the bonds—figuratively and literally—of love and lust."The song "Free Xone" from The Velvet Rope, which portrays same-sex relationships in a positive light, is described by sociologist Shayne Lee as "a rare incident in which a popular black vocalist explores romantic or sensual energy outside the contours of heteronormativity, making it a significant song in black sexual politics." During promotion for Janet, she stated "I love feeling deeply sexual—and don't mind letting the world know. For me, sex has become a celebration, a joyful part of the creative process."Upon the release of Damita Jo, Jackon stated "Beginning with the earlier albums, exploring—and liberating—my sexuality has been an ongoing discovery and theme," adding "As an artist, that's not only my passion, it's my obligation." Stephen Thomas Erlewine has found Jackson's consistent inclusion of sex in her music lacking ingenuity, especially in comparisons to other artists such as Prince, stating "while sex indisputably fuels much great pop music, it isn't an inherently fascinating topic for pop music—as with anything, it all depends on the artist.".
Question: What is the first of the person who, according to Smith, "challenged audiences to see her as a transformed person, from an ingénue to a grow-up, multi-talented celebrity"?
Answer: Janet.
Question: Passage: Pontius Pilate offers to release either Jesus of Nazareth or Barabbas, in keeping with the Passover custom. The crowd gathered for the pardoning chooses Barabbas, and Jesus is condemned to crucifixion. Returning to his friends, Barabbas asks for his lover, Rachel. His friends inform him that Rachel has become a follower of Christ. Rachel soon returns, but she is not happy to see Barabbas.
Barabbas witnesses the crucifixion of Jesus. As Jesus dies, the sky turns black, and Barabbas is shaken. He watches Christ's body sealed in the tomb. On the third morning, Barabbas finds the tomb open. Rachel tells him that Christ has risen, but Barabbas says it is an illusion, or that His followers have stolen the body. He visits the apostles; they do not know where He is, but also believe He is risen.
Rachel preaches in Jerusalem about the Christ. She is stoned to death at the insistence of the priests. Barabbas returns to his criminal ways and robs a caravan transporting several of the priests. He throws stones at one of them rather than fleeing, and is captured by Roman soldiers. The law forbids Pilate from executing someone who has been pardoned, so he sentences Barabbas to lifelong slavery in the sulfur mines of Sicily.
Barabbas survives this hellish existence for the next twenty years. He is chained to Sahak, a sailor who was sent to the mines for allowing slaves to escape. Sahak is a Christian. Sahak at first hates Barabbas for being pardoned instead of "the Master", but the two men eventually become friends. Over time, Sahak becomes too weak to work. As the guards are about to kill him the mine is destroyed in an earthquake. Sahak and Barabbas are the only survivors. Julia, the superstitious wife of the local prefect, considers them blessed. The prefect is due to leave for Rome to be appointed to the Senate. Julia insists that Barabbas and Sahak accompany him for good luck.
Question: What is the last name of the person who sentences someone to lifelong slavery?
Answer:
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Pilate.
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NIv2
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task002_quoref_answer_generation
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fs_opt
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] |
Detailed Instructions: You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Q: È stata una trasformazione senza eguali.
A:
|
他に類を見ないような変革でした
| 9
|
NIv2
|
task1248_ted_translation_it_ja
|
zs_opt
|
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] |
Given a command in a limited form of natural language, provide the correct sequence of actions that executes the command to thus navigate an agent in its environment. A command can be broken down into many different actions. Actions are uppercase and are individual steps that serve as the building blocks for a command. For commands, 'left' and 'right' are used to denote the direction of an action. The word 'opposite' turns the agent backward in the specified direction. The word 'around' makes the agent execute an action while turning around in the specified direction. The word 'and' means to execute the next scope of the command following the previous scope of the command. The word 'after' signifies to execute the previous scope of the command following the next scope of the command. The words 'twice' and 'thrice' trigger repetition of a command that they scope over two times or three times, respectively. There are only six actions: 'I_LOOK', 'I_WALK', 'I_RUN', 'I_JUMP', 'I_TURN_LEFT', and 'I_TURN_RIGHT'. These actions respectively align with the commands 'look', 'walk', 'run', 'jump', 'turn left', and 'turn right'. Actions and commands do not have quotations in the input and output.
Q: look opposite right and turn around left twice
A:
|
I_TURN_RIGHT I_TURN_RIGHT I_LOOK I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT
| 4
|
NIv2
|
task126_scan_structured_text_generation_command_action_all
|
zs_opt
|
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] |
Detailed Instructions: In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: threat and non-threat. Threat is a statement that someone will be hurt or harmed, especially if the person does not do something in particular.
Problem:Comment: Try sociopath!
Solution:
|
Non-threat
| 8
|
NIv2
|
task322_jigsaw_classification_threat
|
zs_opt
|
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] |
Teacher: In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Sentence 1: Jon saw his friend Tom coming out of the grocery store with a bag of fruit. Sentence 2: Tom had been shopping in the store.
Solution: Tom had been shopping for fruit to give Jon.
Reason: The given sentence is a good alteration. If the changed sentence was something like: "Tom had been sleeping in his house in that time", it'd contradict the first sentence. But this given sentence neither agrees with the first sentence, nor contradicts it.
Now, solve this instance: Sentence 1: A woman with an umbrella is jumping in a park. Sentence 2: A woman jumps.
Student:
|
A woman jumps for joy in the park.
| 2
|
NIv2
|
task184_snli_entailment_to_neutral_text_modification
|
fs_opt
|
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] |
Definition: You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. You are required to assign a label 'formal' if there is an absence of emotion and a presence of questions anywhere within the conversation. If such pattern is not found assign the label 'informal'.
Input: Person1: Welcome to Super Stereos . What can I do for you ?
Person2:I'd like to look at your stereo systems . Do you have anything on sale ?
Person1: Yes , this system over here is on sale for $ 1,000 . As you can see , all of the components are brand-name .
Person2:But it doesn't have a turntable . I have a fair number of vinyl records , so I need something to play them on .
Person1: Our selection of stereo systems with turntables is somewhat limited , but we do have this system over here .
Output:
|
formal
| 2
|
NIv2
|
task1533_daily_dialog_formal_classification
|
zs_opt
|
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] |
In this task, you're given the beginning and the ending of a three-part story. Your job is to complete the short story by writing a middle sentence that seamlessly connects the first and last sentence. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a child. Avoid using any irrelevant extra information when creating the middle sentence, and use names (e.g. Jack, Barbara,...) instead of pronouns (e.g. he / she) wherever possible.
One example: Beginning: Helen lived in the state of Washington. Ending: Helen stayed home instead and planned to go another day.
Solution is here: Helen planned to drive to Canada but it started snowing heavily.
Explanation: Generally, people prefer not to drive in bad weather.
Now, solve this: Beginning: Larry realizes he has been spending too much money in restaurants. Ending: Larry is happy that he is going to restaurants less than he used to.
Solution:
|
He started packing his own lunch.
| 6
|
NIv2
|
task067_abductivenli_answer_generation
|
fs_opt
|
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] |
Detailed Instructions: Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.
Q: Context: To examine the association between insomnia with short sleep duration and hypercholesterolemia in Taiwanese adults.', 'Previous studies mostly focused on the association between sleep duration and hyperlipidemia, but the results were not consistent. Besides, very few studies extensively examined the association between insomnia and hypercholesterolemia. This study hypothesized that insomnia with short sleep duration is associated with hypercholesterolemia.', 'Secondary data analysis. This study analysed the latest database of the cross-sectional Nutrition and Health Survey in Taiwan which was released on 2011 (data collected between 2005-2008) and collected data using stratified three-staged probability sampling design.', 'This study analysed 1533 participants aged between 19-64 (733 males and 800 females) and used logistic regression model to calculate the odds ratio and the 95% confidence interval of insomnia with short sleep duration to hypercholesterolemia. Controlled confounders included age, gender, sample weight, body mass index, waist circumference, fasting plasma glucose, hypertension and diabetes.', 'Insomnia with 5-6\xa0hours of sleep duration was significantly associated with hypercholesterolemia. The odds ratio of mild insomnia or moderate/severe insomnia with 5-6\xa0hours of sleep duration to hypercholesterolemia was higher, compared with the reference group (without insomnia and >6\xa0hours of sleep duration).
Answer: Insomnia with short sleep duration was associated with increased odds of hypercholesterolemia. Caregivers in clinical practice should watch out for the effect brought by this novel factor.
A:
|
Is the relationship between insomnia with short sleep duration associated with hypercholesterolemia : a cross-sectional study?
| 9
|
NIv2
|
task845_pubmedqa_question_generation
|
zs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
Example: 1975 - 76年のNBAシーズンは、全米バスケットボール協会の30番目のシーズンでした。
Output: La saison 1975-1976 de la National Basketball Association était la 30e saison de la NBA.
This is a correct and accurate translation from Japanese to French because the translated paraphrase retains the main message that between the years 1975-1976, the 30th NBA season occurred.
New input case for you: 分岐コディス2は毎日更新され、分岐コディス3は6ヶ月ごとに更新されます。
Output:
|
La branche codice 2 est mise à jour quotidiennement et le codice de branche 3 est mis à jour tous les 6 mois.
| 1
|
NIv2
|
task815_pawsx_japanese_french_translation
|
fs_opt
|
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] |
Detailed Instructions: Given a sentence in English language, translate the sentence to Tagalog language keeping the meaning of the original sentence intact.
Problem:English sentence: He presented his law of radiation, stating that, for a given atom or molecule, the emission and absorption frequencies are the same.
Solution:
|
Siya itinanghal ang kanyang batas ng radiation, na nagpapahiwatig na, para sa isang atom o titing, ang paglabas at Absorsyon frequencies ay ang parehong.
| 8
|
NIv2
|
task448_opus_paracrawl_en_tl_translation
|
zs_opt
|
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In this task, you will be presented with a passage and have to answer a question based on your understanding of the events inferred from the passage. Among the entities, try to find the best entity that is most likely to fill in "_" and classify the answers based on options.
(CNN) Republican candidate Donald Trump has a woman problem. Last week, for example: His campaign manager was arrested on assault charges after allegedly grabbing a female reporter; then, Trump infamously told an interviewer that women who have illegal abortions must be punished, quickly retracted the statement and ended up calling in his ex-wife Ivana to try to dig him out of his gender free-for-all. If she still likes him, then why can't we? The numbers are less forgiving than a former spouse, it appears, and Tuesday night's loss in Wisconsin may suggest that Trump's once insurmountable drive to the nomination is wavering.Juliette Kayyem: GOP-leaning "Security Moms" demographic could be area where Donald Trump improves his standingShe says post-9/11, the group has been key in elections, making it tempting for GOP candidates to woo them by playing to fearsKayyem: Clinton can gain their vote by acknowledging their fears and taking a more reasoned approach to keeping America safe
Questions:Only _, as a mother and grandmother, can speak to the emotional fear for the safety of our children that animates so many women voters. (A) CNN (B) Republican (C) Donald Trump (D) Trump (E) Ivana (F) Wisconsin (G) Juliette Kayyem (H) GOP (I) Security Moms (J) Kayyem (K) Clinton (L) America
(K)
A Las Vegas Girl Scouts hiking event was cancelled after a venue overbooked it with a Hillary Clinton campaign rally. Troop 21 raised money and bought tickets in September for the Brownie Hiker Badge class put on by Springs Preserve on Wednesday, however when they showed up they were informed the event was cancelled, Fox 5 reported. The Brownies' troop leader, Cheryl King, said they were told at the door that Springs Preserve representatives had called the Girl Scouts of Southern Nevada last week to cancel the class. 'As I was approaching the building we saw two of the other troops leaving, kind of saddened in the face,' King said.Troop 21 bought tickets in September for the Brownie Hiker Badge class put on by Springs Preserve on WednesdayHowever, when they showed up for the event they were told that it was cancelledThe brownies' troop leader was told at the door that Girl Scouts of Southern Nevada called Springs Reserve last week to cancel the classSprings Preserve said Girl Scouts of Southern Nevada called to cancel due to parents being concerned with traffic issues related to other major eventTroop claim they asked for a refund and Springs Preserve refused but venue said it offered troop leaders a refund
Questions:'_ will offer those who purchased tickets for the class a full refund.' (A) Las Vegas Girl Scouts (B) Hillary Clinton (C) Troop 21 (D) Brownie Hiker Badge (E) Springs Preserve (F) Fox 5 (G) Brownies (H) Cheryl King (I) Girl Scouts of Southern Nevada (J) King (K) Springs Reserve
(E)
(CNN) -- If the United States is serious about thoroughly defeating ISIS, it must -- somehow, some way -- go through Syria. But how? And in what way? Those are the big questions now, as President Barack Obama weighs what to do inside the war-ravaged nation where ISIS leaders are based and where the Islamist terror group rose to prominence. Obama ceded Thursday that "we don't have a strategy yet" for what to do about ISIS inside Syria, with a senior administration official adding that a decision is "a week or so" away. There are certainly options, but none is clear-cut.Obama: U.S. has no military strategy yet on what to do against ISIS in SyriaThere's been no hint of ground forces, but commandos did do a rescue missionAirstrikes are a possibility; a congressman says it's critical U.S. work with locals"There is no such thing as a no-risk strategy," Rep. Adam Smith adds
Questions:If you can't pound _ into submission militarily, the reasoning goes, you can hit it where it hurts: the wallet. (A) CNN (B) United States (C) ISIS (D) Syria (E) Barack Obama (F) Islamist (G) Obama (H) U.S. (I) Adam Smith
|
(C)
| 0
|
NIv2
|
task302_record_classification
|
fs_opt
|
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Given the task definition and input, reply with output. In this task you will be given a list of integers. You should remove any integer that is not prime. A prime integer is an integer that is only divisible by '1' and itself. The output should be the list of prime numbers in the input list. If there are no primes in the input list an empty list ("[]") should be returned.
[184, 443, 599, 852, 337, 971, 118, 874, 587, 384, 539]
|
[443, 599, 337, 971, 587]
| 5
|
NIv2
|
task366_synthetic_return_primes
|
zs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
Classify the given comment into 'Hope Speech' or 'Not Hope Speech'. A hope speech is defined as content that is encouraging, positive or supportive contents and talks about equality, diversity or inclusion
Example: you have encouraged me thank you for sharing
Output: Hope Speech
The given text contains content that is encouraging, positive or supportive contents and talks about equality, diversity or inclusion and is in expected language
New input case for you: My mom’s an engineer. As a girl
Output:
|
Hope Speech
| 1
|
NIv2
|
task679_hope_edi_english_text_classification
|
fs_opt
|
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] |
Definition: In this task you will be given a list of integers. For every element in the list, if the element is even you should divide by two, if the element is odd you should multiply by three then add one. The output should be a list of integers that is the result of applying that logic to the input list.
Input: [146, 106, 44, 157, 127]
Output:
|
[73, 53, 22, 472, 382]
| 2
|
NIv2
|
task206_collatz_conjecture
|
zs_opt
|
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] |
Definition: Generate a question which can yield the answer mentioned in the input. Generated question must be answered by the answer provided in input, without using any extra knowledge.
Input: Context : Lord Chumley is a 1914 short drama film directed by James Kirkwood.
Answer : James Kirkwood
Output:
|
Who was responsible for the direction of Lord Chumley?
| 2
|
NIv2
|
task1326_qa_zre_question_generation_from_answer
|
zs_opt
|
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] |
Detailed Instructions: In this task, you're given two sentences, sentence 1 and sentence 2, and the genre they belong to. Your job is to determine if the two sentences belong to the same genre or not. Indicate your answer with Y and N respectively. Genres available include: face-to-face, government, letters, 9/11, slate, telephone, travel, verbatim, oup, fiction. Sentences belonging to 'face-to-face' genres relate to conversations or dialogues, 'government' encompasses information released from public government websites, 'letters' refers to any written work for philanthropic fundraising, '9/11' relates to information pertaining to the 9/11 attacks, 'oup' includes non-fiction works on the textile industry and child development, 'slate' refers to any cultural topic that appears in the slate magazine, 'telephone' includes telephonic dialogue, 'travel' deals with information in travel guides, 'verbatim' includes short posts regarding linguistics, and 'fiction' includes popular works of fiction like 'The Secret Adversary' etc.
Problem:Sentence 1: They play a shell Take this part of the Social Security tax and convert it into a mandatory savings contribution; take today's benefit and divide it into two parts; give everybody this new account and that minimum guarantee; take this shell and put it there and bring that shell over here, and--hey presto! Sentence 2: R. Telez, Babcock, and Wilcox have no affiliation with one another. Genre: government.
Solution:
|
N
| 8
|
NIv2
|
task204_mnli_same_genre_classification
|
zs_opt
|
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] |
In this task, you are given a sentence in English, and your task is to translate it into Persian.
Q: as you would do if I were your sister.
A:
|
همان گونه که اگر خواهرت بودم میافزودی؟
| 4
|
NIv2
|
task661_mizan_en_fa_translation
|
zs_opt
|
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] |
Given the task definition and input, reply with output. Given a sentence in the Japanese and Filipino language. Your task is check if the Filipino sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Japanese: 写真がMattsのキャンペーン用の印刷物に載った時、背後の人々は写真から削除され、家族が居住を許されることを求めたスローガンは出入国管理に対するものに置き換えられた。
Filipino: Nang lumabas ang litrato sa panulatan ng kampanya ni Matts, ang mga taong nasa likod ay inalis mula sa litrato at ang pamansag ng pagtawag para sa pamilya na papayagang manatili ay pinalitan ng pagtawag para sa pagpipigil ng imigrasyon.
|
Yes
| 5
|
NIv2
|
task1120_alt_ja_fil_answer_generation
|
zs_opt
|
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] |
Given a sentence in Japanese, provide an equivalent paraphrased translation in Chinese that retains the same meaning both through the translation and the paraphrase.
North Downs Wayは、メドウェイバレーウォークまたは高速道路橋の東端にあるメドウェイ高架橋を横切っています。
|
North Downs Way穿过Medway Valley Walk东端的Medway高架桥或Autobahn桥。
| 0
|
NIv2
|
task818_pawsx_japanese_chinese_translation
|
zs_opt
|
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] |
You are given a conversation between two people.'Person1:' and 'Person2:' are used to separate their respective dialogues. You have to classify if there exist more than 2 unique emotions in conversation. If there are more than 2 unique emotions present in the conversation, the output should be classified as '1' else it should be '0'
--------
Question: Person1: Ten sheets of rice paper , 25 brushes , two boxes of oil color and two boxes of water color . All these come up to $ 35.50 , sir .
Person2: Ok , here is $ 50 . Oh , can you make out an invoice for me ?
Person1: Sure , just a minute . Are you an artist , sir ?
Person2: No , I am a teacher . I teach art .
Person1: That must be a very interesting job .
Person2: It is . You must be new here . I do my shopping here regularly , once a week .
Person1: Do you ? Nice to meet you ! And here is the invoice and your change .
Person2: Thank you . Nice to meet you , too .
Answer: 0
Question: Person1: So what do you feel like doing this evening ? How about going to the cinema ?
Person2: Ah , that's a good idea . But I heard the film club of our school would show a film for free . Maybe we don't need to go to the cinema .
Person1: That's good ! I've also heard there will be a party held by the Students ' Union tomorrow evening . Would you like to go with me tomorrow night ?
Person2: I'd like to , but I'm afraid I can't .
Person1: Why ? Do you have to prepare for your examination ? Oh , come on , girl , relaxation is also very important .
Person2: That's not the reason . I have to go to the English Corner tomorrow evening . You know , I've been going there every week .
Person1: Oh , God , I've forgotten it .
Person2: You said you wanted to improve your English , so how about coming with me tomorrow ? I can also introduce some friends to you .
Person1: Oh , no , I don't want to know any more geeks like you .
Person2: They are not geeks . They are also interested in singing , dancing , and so on . They are excellent , and they can always help me a lot .
Person1: Really ? Is there a foreign teacher for every class ?
Person2: It depends . If they are not busy , they will come to join us , and talk with us .
Person1: So you just talk all the time ?
Person2: Of course not . The foreign teachers also teach us English songs , and play games with us .
Person1: That sounds interesting . I'll go with you tomorrow evening .
Person2: You won't be disappointed .
Answer: 1
Question: Person1: Excuse me .
Person2: Yes , Miss , what can I do for you ?
Person1: I ordered my dish about a half an hour ago , but it hasn't arrived yet .
Person2: I'm sorry for that , I'm going to check with the chef right now . Miss , I just checked with the kitchen , and they said your order will be coming right up next . Oh , here comes .
Person1: Thank you .
Person2: Miss , I'm very sorry for the delay , please enjoy this . Free a glass of wine for inconvenience . Again I'm terribly sorry to make you wait so long .
Person1: It doesn't matter .
Answer:
|
1
| 7
|
NIv2
|
task1535_daily_dialog_uniqueness_classification
|
fs_opt
|
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] |
Definition: Translation from English to Telugu.
Input: So what the hell am I supposed to tell O'Keefe?
Output:
|
సోవాట్ది హెల్నేనుకీఫే చెప్పండిచేయాలో am
| 2
|
NIv2
|
task1330_open_subtitles_en_te_translation
|
zs_opt
|
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] |
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to classify the conversation either convey 'No emotion' or 'Happiness' by providing '1' and '0', respectively.
[EX Q]: Person1: Excuse me . I am interested in getting a library card .
Person2: Sure , let me give you an application . You can fill it out right here at the counter .
Person1: OK , here it is .
Person2: Let me take a look at this for you . May I have your driver's license , please ?
Person1: Here's my license and form .
Person2: You seem to have filled the form out all right . Are you familiar with our rules and fines ?
Person1: Yes , I know what to do .
Person2: The hours and limitations are printed on the card and this handout .
Person1: OK .
Person2: Thank you for joining the library ; we look forward to serving you .
[EX A]: 1
[EX Q]: Person1: There is a new coffee shop opening up down the street .
Person2: I hope that they have a good menu . Most coffee shops only have coffee and Danish .
Person1: That's right . You don't drink coffee , do you ?
Person2: No , so it's usually boring to join my friends in the afternoon at a regular coffee shop .
Person1: What kind of things would you like to see on the menu ?
Person2: Maybe a fruit salad and a few different hot sandwiches at least .
Person1: That shouldn't be too difficult . Since this is a small neighborhood , maybe they will take this suggestion .
Person2: Let's try it !
[EX A]: 0
[EX Q]: Person1: What's the weather like in your city ?
Person2: In the summer it gets very hot . The temperature is between often 37 and 40 centigrade . When it is hot we often get rains . The winters are drier .
Person1: The summer temperature usually often reaches about 20 or25 in my city . The rain falls mostly in the winter . And we often get snow .
Person2: What are the temperatures in winter ? In my city it is about 15 or 20 degrees .
Person1: In winter temperature often falls to zero at night temperature can be below that . The streets are often icing in the morning . With high such temperatures you must get some thunderstorms .
Person2: Yeah , we do . In the middle of summer there can be found storms every day usually in the afternoon . I heard your city has a lot of fog , is that true ?
Person1: We do have a few fog days in winter . But I would not say we have a lot of fogs . The sky are usually clearly in your city , are they ?
Person2: Yes , they are like I said we have thunderstorms . But each one usually last a few hours . Then the skys are clear again .
Person1: Have you ever had snow in your city ?
Person2: My grandmother said there was snow once when she was a child . But my parents and I never see it outside of my city .
Person1: The river in my city sometime freeze over . People go ice-skating on it . In summer people go boating on the river . But few people go swimming because it is not very clean .
Person2: As you know , my city is on the coast.the water is also not clean . But people still go swimming all year around . I prefer to sand bath on the beach when the weather is hot and sunning .
[EX A]:
|
0
| 6
|
NIv2
|
task1536_daily_dialog_happiness_classification
|
fs_opt
|
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] |
Teacher:In this task, you're given a short story of five sentences written in natural language. However, the order of the given story is not correct. Your job is to return the correct order for the given five sentences to create a coherent short story with the new order that has the correct flow. Generate your answer using the number of sentences in the correct order, such as '23415'.
Teacher: Now, understand the problem? Solve this instance: Sentence1: Tom began to worry. Sentence2: When he got into the front of the house, he rang the doorbell. Sentence3: He drove as fast as he can although there was a lot of traffic. Sentence4: Tom decided to drive to his girlfriend's house today. Sentence5: No one answered however, the front door was open.
Student:
|
53214
| 6
|
NIv2
|
task300_storycloze_order_generation
|
zs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Example: PPdQTlHHTJEe, DydQTlHHVnmlLu
Output: dQTlHH
Here, 'dQTlHH' is the longest common substring in both the input strings 'PPdQTlHHTJEe' and 'DydQTlHHVnmlLu'.
New input case for you: oiNEYHxbvAb, bcDDdEYHxbCREd
Output:
|
EYHxb
| 1
|
NIv2
|
task600_find_the_longest_common_substring_in_two_strings
|
fs_opt
|
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] |
Teacher:We would like you to assess the QUALITY of each of the following argument (discussing Gun Control) and determine if the argument is Valid or Invalid. A valid argument is clearly interpretable and either expresses an argument, or a premise or a conclusion that can be used in an argument for the topic of gun control. An invalid argument is a phrase that cannot be interpreted as an argument or not on the topic of gun control.
Teacher: Now, understand the problem? Solve this instance: Perhaps if other types of firearms were as strictly regulated as machine guns are then we could make some real progress in reducing gun violence and murder.
Student:
|
Valid
| 6
|
NIv2
|
task150_afs_argument_quality_gun_control
|
zs_opt
|
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] |
Given an open-ended topic (movie name, a persons name, an event, sports, etc) generate a simple trivia-type question.
Example Input: agios nikolaos, crete
Example Output: Aghios Nikolaos is a fishing port and holiday resort on which Greek island?
Example Input: david jason
Example Output: In which UK TV series did Ronnie Barker play Arkwright and David Jason play his nephew Granville?
Example Input: archie bunker
Example Output:
|
Which US television sitcom, starring Carroll O'Connor as Archie Bunker, debuted in January 1971?
| 3
|
NIv2
|
task897_freebase_qa_topic_question_generation
|
fs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Example: Head: PersonX holds PersonY's head<sep>Tail: to be messaged
Output: Yes
This is a good example. As a result of the Head, PersonY will want to be messaged.
New input case for you: Head: PersonX also ordered ___<sep>Tail: out of contol
Output:
|
No
| 1
|
NIv2
|
task1198_atomic_classification_owant
|
fs_opt
|
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] |
Definition: In this task, you are given a text from a social media post. Your task is to classify the given post into two categories: 1) yes if the given post is intentionally offensive, 2) no, otherwise. Also, generate label 'no' for offensive statements that appear to be unintentional, or non-offensive statements that are underhandedly offensive. Warning: the examples and instances may contain offensive language.
Input: @YeIIowbang I hate that faggot he so corny
Output:
|
Yes
| 2
|
NIv2
|
task607_sbic_intentional_offense_binary_classification
|
zs_opt
|
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] |
Q: Given a sentence in the Japanese, provide an equivalent translation in Filipino that retains the same meaning through the translation. In translation, keep numbers as it is.
日本人が２つのソーラーセイルを宇宙空間で展開しており、これは初めてのソーラーセイル試験ではない。
A:
|
វាមិនមែនជាការសាកល្បងបង្ហោះផ្កាយរណបដើរដោយបន្ទះសូឡាលើកទីមួយនោះទេ ដោយប្រទេសជប៉ុនឆ្លាប់បានបង្ហោះផ្កាយរណបដើរដោយបន្ទះសូឡានេះចំនួនពីរចូលក្នុងលំហអាកាសរួចមកហើយ។
| 7
|
NIv2
|
task1121_alt_ja_khm_translation
|
zs_opt
|
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] |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given a sentence in Dutch, generate a new Dutch sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Je kunt een mandje gebruiken om de prullenbak te vervangen.
Solution: Je kunt een mand gebruiken om afval weg te gooien.
Why? This is a good change in the input, because it is semantically similar to the input as both are talking about using a basket to through trash/garbage and the output sentence follows the commonsense knowledge.
New input: Je kunt een fotoblok gebruiken om mezelf op te piepen van iemands verjaardag.
Solution:
|
Je kunt een kalendertabblad gebruiken om mezelf te herinneren aan iemands verjaardag.
| 0
|
NIv2
|
task409_mickey_nl_sentence_perturbation_generation
|
fs_opt
|
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] |
Q: Translate from Hindi to English such that it preserves the original meaning Perform complete translation (partially translated sentences are considered incorrect).
शिक्षा बोर्ड.
A:
|
Board of Education?
| 7
|
NIv2
|
task1323_open_subtitles_hi_en_translation
|
zs_opt
|
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-0.18477129936218262
] |
Instructions: A text is given in Gujarati. Translate it from the Gujarati language to the Panjabi language. The translation must not omit or add information to the original sentence.
Input: 2011ના નિર્ણય, કે જેમાં એએફએસ, કાનપુરને સૈન્યની 8.
Output:
|
90 ਏਕੜ ਡਿਫ਼ੈਂਸ ਜ਼ਮੀਨ ਕੇਂਦਰੀ ਵਿਦਿਆਲਾ ਸੰਗਠਨ ਨੂੰ ਟ੍ਰਾਂਸਫ਼ਰ ਕੀਤੇ ਜਾਣ ਦੀ ਪ੍ਰਵਾਨਗੀ ਦਿੱਤੀ ਗਈ ਸੀ।
| 3
|
NIv2
|
task1043_pib_translation_gujarati_punjabi
|
zs_opt
|
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] |
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Q: ['l', 7331, 'b', 7563, 'K', 8139, 7019, 'g', 9743, 5063, 4213, 2721, 6971, 'F', 'a', 4455, 6945, '8421', '5767', 'P', 'y', 'k', 'U', '4099', '1639', 'M', '2415', '7821', '9365', 'O', 'r', '5485', 'J', '2813', 'k', '7481', '5221', '9233', 'O', 'B', 'M'], [4435, 'u', 'y', 'o', 'Z', 'B', 6853, 'y', 'U', 'n', 'W', 'd', 2125, '8421', '5767', 'P', 'y', 'k', 'U', '4099', '1639', 'M', '2415', '7821', '9365', 'O', 'r', '5485', 'J', '2813', 'k', '7481', '5221', '9233', 'O', 'u', 'X', 'E', 'U', 6691, 1867, 7289, 8993, 'K', 't', 'X', 5817, 'k', 3403]
A:
|
8421, 5767, P, y, k, U, 4099, 1639, M, 2415, 7821, 9365, O, r, 5485, J, 2813, k, 7481, 5221, 9233, O
| 4
|
NIv2
|
task605_find_the_longest_common_subsequence_in_two_lists
|
zs_opt
|
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] |
Teacher:In this task, you're given the beginning and the ending of a three-part story. Your job is to complete the short story by writing a middle sentence that seamlessly connects the first and last sentence. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a child. Avoid using any irrelevant extra information when creating the middle sentence, and use names (e.g. Jack, Barbara,...) instead of pronouns (e.g. he / she) wherever possible.
Teacher: Now, understand the problem? Solve this instance: Beginning: We went to Nantasket Beach in 2005. Ending: We got home safely.
Student:
|
There was an evacuation they put in place.
| 6
|
NIv2
|
task067_abductivenli_answer_generation
|
zs_opt
|
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] |
Part 1. Definition
A text is given in Gujarati. Translate it from the Gujarati language to the Urdu language. The translation must not omit or add information to the original sentence.
Part 2. Example
તેમણે અમેઠીમાં કલાશ્નિકોવ એસોલ્ટ રાયફલનુ ઉત્પાદન કરનાર સંયુક્ત સાહસ ઇન્ડો-રશિયન રાયફલ્સ પ્રા
Answer: مشترکہ وینچر انڈو-روسی رائفلز amethi میں tendorov حملہ Rayfalenu کی پیداوار
Explanation: Correct translation for given sentence. Input sentence means 'Joint Venture Indo-Russian Rifles Producing Tendarov Assault Rayfillenu in Amethi' which is the same as the output sentence.
Part 3. Exercise
આ વિચાર પર ચાલતા નાણાં પંચની ભલામણોને અનુરૂપ મારી સરકારે રાજ્યોના વિકાસ માટે પહેલાની તુલનામાં 10 ટકા વધુ રકમ આપવાનો નિર્ણય કર્યો.
Answer:
|
اس کا مطلب یہ ہے کہ جو لوگ کام کو ایشور سمجھتے ہیں اور اس کی دن رات پوجا کرتےہیں، انہیں دنیا کی تمام خوشیاں اور قناعت نصیب ہوتی ہے۔
| 7
|
NIv2
|
task1001_pib_translation_gujarati_urdu
|
fs_opt
|
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] |
Part 1. Definition
The given sentence contains a typo which could be one of the following four types: (1) swapped letters of a word e.g. 'niec' is a typo of the word 'nice'. (2) missing letter in a word e.g. 'nic' is a typo of the word 'nice'. (3) extra letter in a word e.g. 'nicce' is a typo of the word 'nice'. (4) replaced letter in a word e.g 'nicr' is a typo of the word 'nice'. You need to identify the typo in the given sentence. To do this, answer with the word containing the typo.
Part 2. Example
It is gonig to rain today.
Answer: gonig
Explanation: The word 'gonig' is a typo of the word 'going' as the characters 'i' and 'n' have been swaped.
Part 3. Exercise
a kichen with a fridge and some cabinets in it
Answer:
|
kichen
| 7
|
NIv2
|
task088_identify_typo_verification
|
fs_opt
|
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] |
Teacher:You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Italian.
Teacher: Now, understand the problem? Solve this instance: (笑) そんなに長くはかかりません
Student:
|
(Risate) Ma, credetemi, non ci vorrà molto.
| 6
|
NIv2
|
task1096_ted_translation_ja_it
|
zs_opt
|
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] |
Instructions: In this task, you're given the title of a five-sentence story and the first four sentences. Your job is to write the last sentence of the story such that it seamlessly connects with the rest of the story.
Input: Title: Geometry test. Sentence 1: Mike has a geometry test tomorrow. Sentence 2: He also has baseball practice. Sentence 3: He decided to skip studying. Sentence 4: When he got to class, he did not know anything.
Output:
|
He made a bad grade on his test.
| 3
|
NIv2
|
task216_rocstories_correct_answer_generation
|
zs_opt
|
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] |
instruction:
In this task, you are given a question and a context passage. You have to answer the question based on the given passage.
question:
Who initiates shipping?, Context: The States General of the United Provinces were in control of the Dutch East India Company (VOC) and the Dutch West India Company (WIC), but some shipping expeditions were initiated by some of the provinces, mostly Holland and/or Zeeland.
answer:
some of the provinces
question:
Shabelle Media Network was NOT based in what city?, Context: Other radio stations based in Mogadishu include Mustaqbal Media corporation and the Shabelle Media Network, the latter of which was in 2010 awarded the Media of the Year prize by the Paris-based journalism organisation, Reporters Without Borders (RSF). In total, about one short-wave and ten private FM radio stations broadcast from the capital, with several radio stations broadcasting from the central and southern regions.
answer:
Paris
question:
What did Byron circumnavigate?, Context: Captain John Byron passed through the islands of Tuvalu in 1764 during his circumnavigation of the globe as captain of the Dolphin (1751). Byron charted the atolls as Lagoon Islands. Keith S. Chambers and Doug Munro (1980) identified Niutao as the island that Francisco Mourelle de la Rúa sailed past on 5 May 1781, thus solving what Europeans had called The Mystery of Gran Cocal. Mourelle's map and journal named the island El Gran Cocal ('The Great Coconut Plantation'); however, the latitude and longitude was uncertain. Longitude could only be reckoned crudely as accurate chronometers were unavailable until the late 18th century.
answer:
|
the globe
| 9
|
NIv2
|
task1295_adversarial_qa_question_answering
|
fs_opt
|
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] |
Given the task definition and input, reply with output. Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (correct), CASE_DIFF (case error), PUNCUATION_DIFF (punctuation error), CASE_AND_PUNCUATION_DIFF (both case and punctuation error), STEM_BASED_DIFF (stem word error), DIGIT_DIFF (digit error), INTRAWORD_PUNC_DIFF (intra-word punctuation error), and UNKNOWN_TYPE_DIFF (an error that does not corrrespond to the previous categories)].
['the', 'continuous', 'function', 'G', 'is', 'graphed', "we're", 'interested', 'in', 'the', 'area', 'under', 'the', 'curve', 'between', 'x', 'equals', 'negative', '7', 'and', 'x', 'equals', '7', 'and', "we're", 'considering', 'using', 'Riemann', 'sums', 'to', 'approximate', 'it', 'so', 'this', 'is', 'the', 'area', 'that', "we're", 'thinking', 'about', 'in', 'this', 'light', 'blue', 'color', 'order', 'the', 'areas', 'from', 'least', 'on', 'top', 'to', 'greatest', 'on', 'bottom', 'so', 'this', 'is', 'a', 'screenshot', 'from', '', 'Khan', 'Academy', 'exercise', 'where', 'you', 'would', 'be', 'expected', 'to', 'actually', 'click', 'and', 'drag', 'these', 'around', 'but', "it's", 'just', 'a', 'screenshot', 'so', 'what', "I'm", 'gonna', 'do', 'instead', 'of', 'dragging', 'them', 'around', "I'm", 'just', 'gonna', 'write', 'numbers', 'ordering']
|
['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'CASE_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'DIGIT_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF']
| 5
|
NIv2
|
task1416_youtube_caption_corrections_incorrect_grammar_classification
|
zs_opt
|
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Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. Actions are individual steps that serve as the building blocks for a command. There are only six actions: 'I_LOOK', 'I_WALK', 'I_RUN', 'I_JUMP', 'I_TURN_LEFT', and 'I_TURN_RIGHT'. These actions respectively align with the commands 'look', 'walk', 'run', 'jump', 'turn left', and 'turn right'. For commands, 'left' and 'right' are used to denote the direction of an action. opposite turns the agent backward in the specified direction. The word 'around' makes the agent execute an action while turning around in the specified direction. The word 'and' means to execute the next scope of the command following the previous scope of the command. The word 'after' signifies to execute the previous scope of the command following the next scope of the command. The words 'twice' and 'thrice' trigger repetition of a command that they scope over two times or three times, respectively. Actions and commands do not have quotations in the input and output.
Example Input: I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_RIGHT I_TURN_RIGHT I_TURN_RIGHT
Example Output: turn right thrice after walk around left thrice
Example Input: I_TURN_RIGHT I_TURN_RIGHT I_LOOK I_TURN_RIGHT I_TURN_RIGHT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK
Example Output: look around left thrice after look opposite right twice
Example Input: I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_TURN_RIGHT I_WALK I_RUN I_RUN I_RUN
Example Output:
|
walk around right thrice and run thrice
| 3
|
NIv2
|
task131_scan_long_text_generation_action_command_long
|
fs_opt
|
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] |
In this task, you're given a passage, further information available on a particular linked term from the statement, and a question. Your job is to generate the answer to the question by using the information provided. If there is no clear answer obtainable, output 'none'.
Let me give you an example: Passage: The group was occasionally diverted from strategic missions to carry out air support and interdiction missions. It supported Operation Overlord, the invasion of Normandy by attacking transportation targets, including bridges, along with airfields and strong points in France. On D Day, the squadron and the rest of the 446th Group led the first heavy bomber mission of the day. The 446th aided ground forces at Caen and Saint-Lô during July by hitting bridges, gun batteries, and enemy troops. During Operation Market Garden, the attempt to seize a bridgehead across the Rhine in the Netherlands, the 704th dropped supplies to allied troops near Nijmegen. It struck lines of communications during the Battle of the Bulge. During Operation Varsity in March 1945, it supplied ground and airborne troops near Wesel. The squadron flew its last combat mission on 25 April 1945 against Salzburg, Austria. The group had flown 273 missions and had lost 58 aircraft during the war,
. Link Information: Operation Market Garden was a failed World War II military operation fought in the Netherlands from 17 to 25 September 1944. Question: When did the operation during which the 704th dropped supplies to allied troops near Nijmegen begin?
The answer to this example can be: from 17 to 25 September 1944
Here is why: The passage describes the 704th's actions during Operation Market Garden, and the answer specifies when the operation happened.
OK. solve this:
Passage: Born in Portland, Oregon, Alley received an Artium Baccalaureus from Stanford University in 1952 and was a lieutenant in the United States Army during the Korean War, from 1952 to 1954. He received a Juris Doctor from Stanford Law School in 1957, and was a law clerk on the Supreme Court of Oregon, in Salem, Oregon in 1957, and then in private practice in Portland from 1957 to 1959. He returned to the military as assistant staff judge advocate, U. S. Army Artillery and Missile Center, Fort Sill, Oklahoma, 1959–1960 and then as assistant staff judge advocate, Headquarters, U. S. Army Ryukyu Islands (Okinawa, Japan), 1960–1964. He was in the Thirteenth Career Class, TJAGSA, 1965, and was a member of the faculty of Judge Advocate General's School in Charlottsville, Virginia, from 1965 to 1968. He was a military judge for the U.S. Army Trial Judiciary in Saigon, Republic of Vietnam, from 1968 to 1969, and at Schofield Barracks in Hawaii from 1970 to 1972. He then served on the U.S. Army Court of Military Review in Falls Church, Virginia, from 1972 to 1975, serving as chief trial judge of that court in 1975. He was chief of the Criminal Law Division, Office of the Judge Advocate General, Department of the Army, in Washington, D.C. from 1975 to 1978, and in the United States Army, judge advocate, in Heidelberg, Germany, from 1978 to 1981. He was dean and professor of law at the University of Oklahoma College of Law, in Norman, Oklahoma, from 1981 to 1985.
Link Information: Established in 1893 Question: In what year was the school established were Alley received his Juris Doctor.
Answer:
|
Answer: 1893
| 8
|
NIv2
|
task238_iirc_answer_from_passage_answer_generation
|
fs_opt
|
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] |
Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
[Q]: សភាតំណាងរាស្រ្តបានកំពុងជជែកច្បាបកែប្រែបីបួនដែលបានស្នើឡើងទៅកាន់គម្រោងច្បាប់កែទម្រង់រដ្ឋាភិបាលក្នុងតំបន់ដែលមានគោលបំណងក្នុងការផ្លាស់ប្ដូរតំរូវការបន្ទះឆីបតូចៗ។
[A]: 議会は、マイクロチップ規制を変更することを目的とした地方政府法改革法案へのいくつかの修正提案について議論してきた。
[Q]: អ្នកសង្កេតការណ៍នយោបាយបានអធិបាយថាការបោះឆ្នោតនេះគឺមានលក្ខណៈប្រកិតគ្នាខ្លាំងរវាងអ្នកទាំងពីរ។
[A]: 政治評論家は今回の選挙は両者どちらとも決めがたい接戦だとコメントしている。
[Q]: មេជឺរបាននិយាយថានឹងមិនមានរូបិយប័ណ្ណរួមរវាងស្កុតឡែនឯករាជ្យថ្មីមួយនេះនិងចក្រភពអង់គ្លេសក្រោយការបំបែកទេ: "រូបិយប័ណ្ណរួមមួយ ដែលSNP[គណបក្សជាតិស្កុតឡេន]សន្មត់ថានឹងចរចារបាន នឹងតម្រូវឱ្យចក្រភពអង់គ្លេសធានាបំណុលស្កុតឡេន។
[A]:
|
メージャーは新しく独立するスコットランドと分離後の英国のあいだに通貨同盟はありえないと言い、「スコットランド民族党が交渉の余地があると思っている通貨同盟は英国にスコットランドの負債を引き受けることを要求する」と言った。
| 5
|
NIv2
|
task1122_alt_khm_ja_translation
|
fs_opt
|
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] |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence in either Spanish or English. Your task is to determine the language of the input sentence. Input sentences can only be in Spanish or English, and they cannot be in two languages at the same time.
Even though we know that incineration is not the ideal solution, it represents an important advance for many authorities which have invested heavily to develop modern management of the municipal service for domestic and similar waste.
Output:
|
English
| 1
|
NIv2
|
task533_europarl_es-en_language_identification
|
zs_opt
|
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] |
The task is to generate the correct answer for a given math problem.
Let me give you an example: a multiple choice test consists of 4 questions, and each question has 5 answer choices. in how many r ways can the test be completed if every question is unanswered ?
The answer to this example can be: 625
Here is why: Total r of 5 * 5 * 5 * 5 = 5 ^ 4 = 625 ways to answer all of them. Therefore, the answer is 625.
OK. solve this:
Problem: a small pool filled only with water will require an additional 300 gallons of water in order to be filled to 80 % of its capacity . if pumping in these additional 300 gallons of water will increase the amount of water in the pool by 25 % , what is the total capacity of the pool in gallons ?
Answer:
|
1875
| 8
|
NIv2
|
task1726_mathqa_correct_answer_generation
|
fs_opt
|
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] |
You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Portugese.
[Q]: الفن يجب ان يكون احد الادوات التي نطور مجتمعنا من خلاله
[A]: A arte deveria ser uma das ferramentas para melhorarmos a nossa sociedade.
[Q]: هذا من سي بي سي سانداي مورنينغ - تم عرضه من أسبوعين تقريبا.
[A]: Isto é o Sunday Morning da CBS — estrearam há cerca de duas semanas.
[Q]: سترى لماذا — للتلاعب في نتائج البحث.
[A]:
|
Porquê? Para manipularem o resultado da pesquisa.
| 5
|
NIv2
|
task1109_ted_translation_ar_pt
|
fs_opt
|
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] |
In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
One example is below.
Q: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
A: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Rationale: Here, the generated sentence interprets given logical form correctly that 3rd maximum should be selected from given table rows.
Q: eq { hop { argmax { all_rows ; number of episodes } ; english title ( chinese title ) } ; dark tales ii 聊齋 ( 貳 ) } = true
A:
|
select the row whose number of episodes record of all rows is maximum . the english title chinese title record of this row is dark tales ii 聊齋 貳 .
| 9
|
NIv2
|
task110_logic2text_sentence_generation
|
fs_opt
|
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] |
Teacher: In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: toxic and non-toxic. Toxicity is defiend as anything that is rude, disrespectful, or unreasonable that would make someone want to leave a converation.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Comment: i am just sorry that khadr didnt get a bullet in the head before he blew the head off that innocent father because his islamic boogie skywizard told him to.
Solution: Toxic
Reason: This is a toxic comment because it advocates acts of violence.
Now, solve this instance: Comment: Idiot comment of the day. Just proves gun-grabbers have no logic.
Student:
|
Toxic
| 2
|
NIv2
|
task327_jigsaw_classification_toxic
|
fs_opt
|
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] |
Definition: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Input: עכשיו, לבסוף התברר שמדובר בשירבוט של ביל גייטס.
Output:
|
Poi si è scoperto che erano gli scarabocchi di Bill Gates.
| 2
|
NIv2
|
task1111_ted_translation_he_it
|
zs_opt
|
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] |
In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: sexual-explicit and non-sexual-explicit. A comment is considered sexual-explicit if it explicitly portrays sexual matters.
Example: Comment: President lied under oath about consensual sex...
Not the same thing as rape.
Example solution: Sexual-explicit
Example explanation: This comment explicitly mentions "consensual sex" and "rape", and thus is sexual-explicit.
Problem: Comment: Yep and I have a bond on Nkandla and I have no knowledge of alterations to the homestead or have sexual relations with that woman!!!
|
Solution: Sexual-explicit
| 5
|
NIv2
|
task323_jigsaw_classification_sexually_explicit
|
fs_opt
|
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] |
Detailed Instructions: In this task, you are given an input i,A where i is an integer and A is an array. You need to find every ith element of A starting with the 1st element.
Problem:4, ['w', '9053', 'S', '171', '5407', '193', '5755', '495', 'v', '4169', 'V', '5197', '1097', 'j', 'x', '7483', 'z', '2027', '8441', '1867', '3979', '7885', 'm', '1965', 'g', 'e', 'T', '7205', 'j', '8665', 'T', '6327', 'p', '6275', '9827', 'J', '3473', 'b', '8939', 'p', '2825', '1031']
Solution:
|
w, 5407, v, 1097, z, 3979, g, j, p, 3473, 2825
| 8
|
NIv2
|
task1542_every_ith_element_from_starting
|
zs_opt
|
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] |
In this task, you are given a sentence in the Hindi language and a corresponding English translation of the Hindi sentence. Your task is to generate a label "Yes" if the translation is correct, otherwise generate label "No". In the translation, English sentence should preserve the number as it is and it should be in sentence case (capitalize only the first word of each sentence and noun).
Let me give you an example: Hindi: पहले दो को अविश्वसनीय मानकर बाकी पांच मुखबिरों के आधार पर मुकदमा चलाया गया|
English: The first two were found unreliable and the prosecution case rested mainly on the evidence of the remaining five approvers .
The answer to this example can be: Yes
Here is why: Hindi sentence is properly converted into English sentence because the Hindi sentence also says that the first two were judged to be untrustworthy, thus the prosecution relied heavily on the testimony of the remaining five approvers. Also, the translated sentence is in a sentence case.
OK. solve this:
Hindi: दीवाली यही चरितार्थ करती है- असतो माऽ सद्गमय तमसो माऽ ज्योतिर्गमय।
English: Diwali depicts this sanskrit sentence - Asato maa sad gamay, tamso ma jyotir gamay.(take us from untruth to truth, take us from darkness[ignorance] to light[knowledge])
Answer:
|
Yes
| 8
|
NIv2
|
task426_hindienglish_corpora_hi-en_classification
|
fs_opt
|
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] |
Detailed Instructions: Given a document, generate a short title of the document. The title should convey the main idea/event/topic about which the document is being written. Note that URLs in the text have been replaced with [Link].
Q: Spanish Prime Minister Mariano Rajoy vows that his government will not allow Catalonia which represents a fifth of Spain's economy to break away from the rest of the country.
In an interview with the Spanish newspaper El Pais published Sunday Rajoy said that he will consider employing any measure "allowed by the law" to stop the region's separatists.
Rajoy said that includes the application of Article 155 of the Spanish Constitution which would allow the central government to take control of the governance of a region "if the regional government does not comply with the obligations of the Constitution."
"The ideal situation would be that I don't have to find drastic solutions but for that to happen there will have to be some rectifications (by Catalan leaders) " Rajoy said.
Rallies were held Saturday in Madrid Barcelona and other cities to demand that Rajoy and Puigdemont negotiate to find a solution to Spain's worst political crisis in nearly four decades.
A:
|
Hundreds of thousands rally against Catalonia secession
| 9
|
NIv2
|
task418_persent_title_generation
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zs_opt
|
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] |
In this task, you are given a text of article and corresponding title of an article. Your task is to generate label "yes" if headline (title) is right for article, otherwise generate "no".
Let me give you an example: Article: australia 's current account deficit shrunk by a record #.## billion dollars -lrb- #.## billion us -rrb- in the june quarter due to soaring commodity prices , figures released monday showed . Title: australian current account deficit narrows sharply
The answer to this example can be: yes
Here is why: This headline is appropriate for the given article text because the focus of this article is australian current accounts. Hence, the label is 'yes'.
OK. solve this:
Article: oil prices rose on friday as hurricane ike forced the closure of energy production facilities in the gulf of mexico , traders said . Title: dutch chip maker nxp announces #,### job cuts
Answer:
|
no
| 8
|
NIv2
|
task289_gigaword_summarization
|
fs_opt
|
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] |
Instructions: You are given a sentence in Persian. Your job is to translate the Farsi sentence into Japanese.
Input: یکجور شوخی بود ، چون مشتق گیری دوگانه از کلمه ای یونانی است.
Output:
|
ある種のジョークありギリシャ語から派生した二つの意味を持っています
| 3
|
NIv2
|
task1266_ted_translation_fa_ja
|
zs_opt
|
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] |
In this task, you are given a context and four options. Each option is a suggested ending for the context. You should read the context and pick the best ending for the context. Please answer with "A", "B", "C", and "D".
Q: [header] How to style hair with hot rollers [title] Get the rollers ready. [step] Go ahead and plug in the hot rollers so that they're fully heated by the time you're ready to put them in your hair. If this is your first time using your set of rollers, read the manufacturer's instructions to make sure you use the equipment properly. <sep> (A) [title] Spray your hair with gentle hold hairspray. [step] Start with dry hair, since your hair won't hold curls if you use this method with wet hair. (B) [substeps] Always hold the handle of the steam wand between your wrist and the rollers. Never hold the handle of a curling iron at a normal straight line. (C) [substeps] Make sure your hair is fully washed and dry to avoid taking off any primer or styling gel. [title] Brush your hair while in the rollers. (D) [substeps] For thicker hair, use an extension. If your hair is thick, use an extension with one end attached to the round back of your hair.
A:
|
A
| 4
|
NIv2
|
task1389_hellaswag_completion
|
zs_opt
|
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] |
Detailed Instructions: Given a phrase describing the relationship between two words, extract the words and the lexical relationship between them. The relation has to be of the type 'MemberOf', 'MadeOf', 'Synonym', 'Entails', 'HasA', 'HasProperty', 'PartOf', 'Antonym' or 'IsA'. The output should have the format: word1 relation word2.
Q: lie can be used as the opposite of sit
A:
|
lie Antonym sit
| 9
|
NIv2
|
task1510_evalution_relation_extraction
|
zs_opt
|
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] |
Definition: You are given a sentence in Polish. Your job is to translate the Polish sentence into Arabic.
Input: Następnie dane wysyłane są do systemu operacyjnego, gdzie łączone są z kartoteką pacjenta umieszczoną w bazie danych w centrali, dajmy na to, w Stanach Zjednoczonych.
Output:
|
ثم يذهب إلى مركز عمليات الشبكة حيث يحصلون على البيانات من قواعد البيانات الخاصة بك كمريض التي وضعت في موقع مركزي ما ، مثلا ، في الولايات المتحدة.
| 2
|
NIv2
|
task1259_ted_translation_pl_ar
|
zs_opt
|
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] |
In this task, you are given an input list A. If the count of numbers is more than that of alphabets in the list, answer 'Numbers Win'. If the count of alphabets is more than that of numbers in the list, answer 'Alphabets Win'. If the count of numbers is same as that of alphabets in the list, answer 'Numbers and Alphabets are Tied'.
One example is below.
Q: ['238', 'h', '92', 'U', '2799']
A: Numbers Win
Rationale: Here, the count of alphabets is 2, and that of numbers is 3. Since there are more numbers than alphabets, hence the answer is 'Numbers Win'.
Q: ['2863', '5261', 'y', 'G', '8689', '885', 'g', '1979', 'o', '3221', '3327', '573', '7951', 'Z', 'k']
A:
|
Numbers Win
| 9
|
NIv2
|
task523_find_if_numbers_or_alphabets_are_more_in_list
|
fs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.
Example: Context: Chronic rhinosinusitis (CRS) is a heterogeneous disease with an uncertain pathogenesis. Group 2 innate lymphoid cells (ILC2s) represent a recently discovered cell population which has been implicated in driving Th2 inflammation in CRS; however, their relationship with clinical disease characteristics has yet to be investigated. The aim of this study was to identify ILC2s in sinus mucosa in patients with CRS and controls and compare ILC2s across characteristics of disease. A cross-sectional study of patients with CRS undergoing endoscopic sinus surgery was conducted. Sinus mucosal biopsies were obtained during surgery and control tissue from patients undergoing pituitary tumour resection through transphenoidal approach. ILC2s were identified as CD45(+) Lin(-) CD127(+) CD4(-) CD8(-) CRTH2(CD294)(+) CD161(+) cells in single cell suspensions through flow cytometry. ILC2 frequencies, measured as a percentage of CD45(+) cells, were compared across CRS phenotype, endotype, inflammatory CRS subtype and other disease characteristics including blood eosinophils, serum IgE, asthma status and nasal symptom score. 35 patients (40% female, age 48 ± 17 years) including 13 with eosinophilic CRS (eCRS), 13 with non-eCRS and 9 controls were recruited. ILC2 frequencies were associated with the presence of nasal polyps (P = 0.002) as well as high tissue eosinophilia (P = 0.004) and eosinophil-dominant CRS (P = 0.001) (Mann-Whitney U). They were also associated with increased blood eosinophilia (P = 0.005). There were no significant associations found between ILC2s and serum total IgE and allergic disease. In the CRS with nasal polyps (CRSwNP) population, ILC2s were increased in patients with co-existing asthma (P = 0.03). ILC2s were also correlated with worsening nasal symptom score in CRS (P = 0.04).
Question: Are group 2 innate lymphoid cells ( ILC2s ) increased in chronic rhinosinusitis with nasal polyps or eosinophilia?
Output: As ILC2s are elevated in patients with CRSwNP, they may drive nasal polyp formation in CRS. ILC2s are also linked with high tissue and blood eosinophilia and have a potential role in the activation and survival of eosinophils during the Th2 immune response. The association of innate lymphoid cells in CRS provides insights into its pathogenesis.
The output says that ILC2s are elevated in patients with CRSwNP and that they may drive nasal polyp formtion in CRS. The output also says that ILC2s are linked with blood eosinophilia and hence, it completely answers the question on the basis of the information in the context.
New input case for you: Context: To apply clarithromycin as an immunomodulatory treatment in experimental infection caused by pan-resistant Klebsiella pneumoniae.', 'Acute pyelonephritis was induced in 80 rabbits after inoculation of the test isolate in the renal pelvis. Rabbits were divided into eight groups, with 10 animals in each group. In groups A-D, therapy was administered simultaneously with bacterial challenge as follows: A, controls; B, intravenous clarithromycin; C, amikacin; and D, both agents. In groups E-H, therapy was administered 24 h after bacterial challenge as follows: E, controls; F, intravenous clarithromycin; G, amikacin; and H, both agents. Blood was sampled for estimation of tumour necrosis factor-alpha (TNF-alpha) and malondialdehyde (MDA); monocytes were isolated for determination of intracellular activity of caspase-3 and ex vivo TNF-alpha secretion. Four days after bacterial challenge, animals were sacrificed for quantitative cultures and biopsies of organs.', 'Serum TNF-alpha at 48 h was lower in groups B, C and D compared with group A. Activity of caspase-3 of monocytes was lower at 48 h in group D compared with group A. Bacterial loads of liver and spleen were decreased in group D compared with those of group A. The numbers of inflammatory cells of spleen of group B were lower compared with those of group A; those of kidney and mesenteric lymph nodes of group D were lower than those of group A. Serum MDA of group H was lower than that of group E and serum TNF-alpha of group F was lower compared with that of group E. TNF-alpha of monocyte supernatants and activity of caspase-3 of monocytes of group F were lower than those of group E. Bacterial tissue loads did not differ among groups E, F, G and H. The numbers of inflammatory cells of liver of groups F and H were lower compared with those of group E; those of kidney of groups F, G and H were lower compared with those of group E.\Question: Is clarithromycin an effective immunomodulator in experimental pyelonephritis caused by pan-resistant Klebsiella pneumoniae?
Output:
|
Clarithromycin administered intravenously in experimental infection caused by pan-resistant K. pneumoniae attenuated systemic inflammatory response and local tissue damage. This effect is probably attributed to immunomodulatory intervention on blood monocytes.
| 1
|
NIv2
|
task849_pubmedqa_answer_generation
|
fs_opt
|
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] |
Part 1. Definition
In this task, you are given a sentence from the Quran in Persian, and your task is to translate it into English.
Part 2. Example
و همان کسى که جفتها را یکسره آفرید، و براى شما از کشتیها و دامها [وسیلهاى که] سوار شوید قرار داد.
Answer: He who created pairs of everything, and fashioned for you boats and beasts on which you ride,
Explanation: This is a good example. The above sentence is correctly translated from Persian to English.
Part 3. Exercise
پروردگار آسمانها و زمین و آنچه میان آن دو است، بخشایشگرى که کس را یاراى خطاب با او نیست.
Answer:
|
The Lord of the heavens and the earth, and all that lies between them, most benevolent, to whom none may dare address a word.
| 7
|
NIv2
|
task657_quran_fa_en_translation
|
fs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
A text is given in Panjabi. Translate it from the Panjabi language to the Tamil language. The translation must not omit or add information to the original sentence.
Example: கவுஷிக் கங்குலி
Output: ਕੌਕਸ ਗਰੂਕੁਲੀ
Correct translation for given sentence. Input sentence means 'Causk gunkuli' which is the same as the output sentence.
New input case for you: 2019) நடைபெறவுள்ள 15 ஆவது வெளிநாடு வாழ் இந்தியர்கள் தின மாநாட்டை பிரதமர் திரு நரேந்திர மோடி துவக்கி வைக்கவுள்ளார்.
Output:
|
ਪ੍ਰਧਾਨ ਮੰਤਰੀ ਸ੍ਰੀ ਨਰੇਂਦਰ ਮੋਦੀ ਕੱਲ੍ਹ ਵਾਰਾਣਸੀ, ਉੱਤਰ ਪ੍ਰਦੇਸ਼ ਵਿੱਚ ਹੋਣ ਵਾਲੀ 15ਵੀਂ ਪ੍ਰਵਾਸੀ ਭਾਰਤੀਯ ਦਿਵਸ (ਪੀਬੀਡੀ) ਕਨਵੈਨਸ਼ਨ ਦਾ ਉਦਘਾਟਨ ਕਰਨਗੇ।
| 1
|
NIv2
|
task1016_pib_translation_tamil_punjabi
|
fs_opt
|
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] |
Detailed Instructions: In this task, you need to reverse the order of words in the given sentence.
Q: Sentence: road signs on highway in foreign country on a foggy day
A:
|
day foggy a on country foreign in highway on signs road
| 9
|
NIv2
|
task376_reverse_order_of_words
|
zs_opt
|
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Teacher: In this task, you will be presented with a passage and have to answer a question based on your understanding of the events inferred from the passage. Among the entities, try to find the best entity that is most likely to fill in "_" and classify the answers based on options.
Teacher: Now, understand the problem? If you are still confused, see the following example:
For four years we have waited expectantly for the pitter patter of tiny paws. Soon, that wait could finally be over. Tian Tian, the UK's only female giant panda, has conceived and could give birth to a cub as early as August. However Edinburgh Zoo, where the pandas live, have warned people 'not to get too excited' as the process is 'extremely complex'. Moreover, on the two previous occasions keepers inseminated Tian Tian - whose name means 'Sweetie' - she has failed to produce a panda cub. She was artificially inseminated again in March this year, but keepers at the zoo say implantation - when a fertilised egg attaches to the uterus - has not yet occurred.Tian Tian has conceived and could give birth to a cub as early as AugustShe has been inseminated twice before but so far failed to produce a cubTian Tian and Yang Guang arrived in 2011 from China to great fanfareOn loan at £600k a year, became first giant pandas to live in UK for 17 years
Questions:Under the terms of the agreement any cubs will return to _ at the age of two, the age at which they would normally leave their mother in the wild. (A) Tian Tian (B) UK (C) Edinburgh Zoo (D) Sweetie (E) Yang Guang (F) China
Solution: (F)
Reason: This is a good example. Based on the passage, any cubs will return to China at the age of two
Now, solve this instance: The parents of two-year-old Roman Campbell, who was tragically killed in a house fire on his birthday in May, have spoken out about the damage done to a luxury Gold Coast mansion they were gifted by politician Clive Palmer. This week the rental property's owners discovered the once sparkling house abandoned with around $100,000 worth of damage – including blood and faeces in the carpet, holes in the walls and cupboards ripped off their hinges. Speaking to A Current Affair, Belinda Warwick and Jared Campbell said much of the damage done to the home during the six months they lived there rent-free was through the 'pure frustration' of losing a child.Two-year-old Roman died in house fire in Beenleigh, Queensland, on his birthday in MayClive Palmer secured a beautiful home for Roman's grief-stricken parents in Helensvale on the Gold CoastRoman's father tried to save him but the toddler was trapped in the back of the houseOn Wednesday the Gold Coast mansion was found completely trashed, with doors ripped of hingesA car bought for the family of six was also found trashed and abandoned outside the property
Questions:'I've lost a son and I couldn't explain it,' Mr _ added. (A) Roman Campbell (B) Gold Coast (C) Clive Palmer (D) A Current Affair (E) Belinda Warwick (F) Jared Campbell (G) Roman (H) Beenleigh (I) Queensland (J) Helensvale
Student:
|
(F)
| 2
|
NIv2
|
task302_record_classification
|
fs_opt
|
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] |
You will be given a definition of a task first, then some input of the task.
The task is to generate the correct answer for a given math problem.
Problem: a “ palindromic integer ” is an integer that remains the same when its digits are reversed . so , for example , 43334 and 516615 are both examples of palindromic integers . how many 6 - digit palindromic integers are both even and greater than 500,000 ?
Output:
|
200
| 1
|
NIv2
|
task1726_mathqa_correct_answer_generation
|
zs_opt
|
[
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1.1136046648025513,
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0.03442718833684921,
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0.44395703077316284,
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] |
This task is about translating a given Yoruba language sentence to English.
One example is below.
Q: Lóde òní gbajúbajà ni àwọn àṣẹ CC lórí ayélujára tí àwọn oníṣẹ́-ọpọlọ jákèjádò ilé-ayé sì ń lò wọ́n fún èyí-ò-jọ̀yìí nǹkan tí o kò lérò.
A: Today CC licenses are prevalent across the web and are used by creators around the world for every type of content you can imagine.
Rationale: This is a good example because the Yoruba sentence has been translated correctly into English.
Q: Ìṣòro kan wáyé nípa àtúntò àwọn ìkànnì náà
A:
|
There was a problem reordering the channels
| 9
|
NIv2
|
task1686_menyo20k_translation
|
fs_opt
|
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