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instruction:
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.
question:
Context: Excessive infant crying, or infantile colic, is a common and often stress-inducing problem for parents that can ultimately result in child abuse. From previous research it is known that maternal depression is related to excessive crying, but so far little is known about the influence of paternal depression.', "In a prospective, population-based study, we obtained information on both maternal and paternal depressive symptoms at 20 weeks of pregnancy by using the Brief Symptom Inventory. Parental depressive symptoms were related to excessive crying in 4426 two-month-old infants. The definition of excessive crying was based on the widely used Wessel's criteria (ie, crying >3 hours for >3 days in the past week).", 'After adjustment for depressive symptoms of the mother and relevant confounders, we found a 1.29 (95% confidence interval: 1.09-1.52) higher risk of excessive infant crying per SD of paternal depressive symptoms.\Question: Are paternal depressive symptoms during pregnancy related to excessive infant crying?
answer:
Our findings indicate that paternal depressive symptoms during pregnancy might be a risk factor for excessive infant crying. This finding could be related to genetic transmission, interaction of a father with lasting depressive symptoms with the infant, or related indirectly through contextual stressors such as marital, familial, or economic distress.
question:
Context: RNA editing is the process whereby an RNA sequence is modified from the sequence of the corresponding DNA template. In the mitochondria of land plants, some cytidines are converted to uridines before translation. Despite substantial study, the molecular biological mechanism by which C-to-U RNA editing proceeds remains relatively obscure, although several experimental studies have implicated a role for cis-recognition. A highly non-random distribution of nucleotides is observed in the immediate vicinity of edited sites (within 20 nucleotides 5' and 3'), but no precise consensus motif has been identified.", "Data for analysis were derived from the the complete mitochondrial genomes of Arabidopsis thaliana, Brassica napus, and Oryza sativa; additionally, a combined data set of observations across all three genomes was generated. We selected datasets based on the 20 nucleotides 5' and the 20 nucleotides 3' of edited sites and an equivalently sized and appropriately constructed null-set of non-edited sites. We used tree-based statistical methods and random forests to generate models of C-to-U RNA editing based on the nucleotides surrounding the edited/non-edited sites and on the estimated folding energies of those regions. Tree-based statistical methods based on primary sequence data surrounding edited/non-edited sites and estimates of free energy of folding yield models with optimistic re-substitution-based estimates of approximately 0.71 accuracy, approximately 0.64 sensitivity, and approximately 0.88 specificity. Random forest analysis yielded better models and more exact performance estimates with approximately 0.74 accuracy, approximately 0.72 sensitivity, and approximately 0.81 specificity for the combined observations.\Question: Do simple statistical models predict C-to-U edited sites in plant mitochondrial RNA?
answer:
Simple models do moderately well in predicting which cytidines will be edited to uridines, and provide the first quantitative predictive models for RNA edited sites in plant mitochondria. Our analysis shows that the identity of the nucleotide -1 to the edited C and the estimated free energy of folding for a 41 nt region surrounding the edited C are the most important variables that distinguish most edited from non-edited sites. However, the results suggest that primary sequence data and simple free energy of folding calculations alone are insufficient to make highly accurate predictions.
question:
Context: Collagenous colitis (CC) is a major cause of chronic non-bloody diarrhoea, particularly in the elderly female population. The aetiology of CC is unknown, and still poor is the understanding of its pathogenesis. This possibly involves dysregulated inflammation and immune-mediated reactions in genetically predisposed individuals, but the contribution of genetic factors to CC is underinvestigated. We systematically tested immune-related genes known to impact the risk of several autoimmune diseases for their potential CC-predisposing role.', 'Three independent cohorts of histologically confirmed CC cases (N=314) and controls (N=4299) from Sweden and Germany were included in a 2-step association analysis. Immunochip and targeted single nucleotide polymorphism (SNP) genotype data were produced, respectively, for discovery and replication purposes. Classical human leucocyte antigen (HLA) variants at 2-digit and 4-digit resolution were obtained via imputation from single marker genotypes. SNPs and HLA variants passing quality control filters were tested for association with CC with logistic regression adjusting for age, sex and country of origin.', 'Forty-two markers gave rise to genome-wide significant association signals, all contained within the HLA region on chromosome 6 (best p=4.2×10\Question: Does dense genotyping of immune-related loci identify HLA variants associated with increased risk of collagenous colitis?
answer:
|
HLA genotype associates with CC, thus implicating HLA-related immune mechanisms in its pathogenesis.
| 9
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NIv2
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task849_pubmedqa_answer_generation
|
fs_opt
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] |
In this task, you're given a text which is the body of the document. Indicate your answer as "Yes" if the text is about a person, otherwise indicate your answer as "No". Don't generate anything else apart from "Yes" or "No". Pay attention that for your answer to be "Yes", the passage should be generally about a person. Mentions of people in the text don't necessarily mean the text is about a person.
--------
Question: Text: Lü Jiangang (simplified Chinese: 吕建刚; traditional Chinese: 呂建剛; pinyin: Lǚ Jiàngāng; born 19 February 1979 in Tianjin China) is a Chinese baseball player who was a member of Team China at the 2008 Summer Olympics. He was the winning pitcher against Chinese Taipei that was the Chinese Team's only win from the Olympics. He also pitched for China at the 2009 World Baseball Classic. He beat Chinese Taipei again in this tournament.
Answer: Yes
Question: Text: Ellis Gibbs Arnall (March 20 1907 in Newnan Georgia – December 13 1992) was an American politician a liberal[citation needed] Democrat who served as the 69th Governor of the U.S. state of Georgia from 1943 to 1947.
Answer: Yes
Question: Text: Julien Clerc pronounced: [ʒy.ljɛ̃ klɛʁ] (4 October 1947) born as Paul Alain Leclerc is a famous French singer and songwriter.
Answer:
|
Yes
| 7
|
NIv2
|
task632_dbpedia_14_classification
|
fs_opt
|
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] |
In this task, you are given a question and answer for that. The answer will fill in the blank or will complete the unfinished question. Your task is to provide an explanation based on the given question or fill-in-the-blank statement, and answer.
One example: Question: The government of Canada is considering implementing less carbon taxes across the country. If these taxes were implemented, the amount of carbon dioxide emissions in the country would be expected to
Answer: rise
Solution is here: The carbon taxes encourage people to use less fossil fuel, which reduces carbon dioxide emissions.
Explanation: As mentioned in the input Question and Answer, the output statement constructs the explanation correctly. By decreasing the taxes, carbon dioxide emissions will rise, so the explanation is correct.
Now, solve this: Question: Objects that are farther apart have a _____ force of gravity.
Answer: weaker
Solution:
|
Objects that are closer together have a stronger force of gravity.
| 6
|
NIv2
|
task223_quartz_explanation_generation
|
fs_opt
|
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] |
instruction:
In this task, you're given an open-domain question. Your task is to provide an answer to the given question. There is only one unique answer for each question. Your answer should be short, and refer to an entity, date, number, etc. Do not put your answer in the context of a sentence.
question:
Who played zuzu in it's a wonderful life?
answer:
Karolyn Grimes
question:
Who was mission san juan capistrano named after?
answer:
Saint John of Capistrano
question:
When did the last person from the titanic die?
answer:
|
May 31, 2009
| 9
|
NIv2
|
task669_ambigqa_answer_generation
|
fs_opt
|
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] |
Detailed Instructions: In this task, you are given an input list A comprising of numbers and alphabets. You need to extract and sort the unique alphabets in the list. The alphabets in the input list will only be in lowercase. Return -1 if there is no alphabet in the input list.
Q: ['73', 'l', 'g', '221', 'q', '6011', '1001', '539', 'h', 'z', '7777', 'p', 't', 'v', 'y', 'o', 'o', '4839', '2317', 'k', '7613', 'f', '5985']
A:
|
f, g, h, k, l, o, p, q, t, v, y, z
| 9
|
NIv2
|
task636_extract_and_sort_unique_alphabets_in_a_list
|
zs_opt
|
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] |
Instructions: The task is about translation from Telugu to English. While performing the translation you must preserve the original meaning. Do not include any words which are only limited to your native place.
Input: మీ మనసును చేయండి.
Output:
|
Make up your mind.
| 3
|
NIv2
|
task1324_open_subtitles_te_en_translation
|
zs_opt
|
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] |
Teacher:Given a sentence in the Japanese, provide an equivalent translation in Bahasa Indonesia that retains the same meaning through the translation. In translation, keep numbers as it is.
Teacher: Now, understand the problem? Solve this instance: 訴訟は、懲罰的な罰金に加えて、ＡT＆Ａの顧客一人あたり２万２０００ドルの損害賠償を求めている。
Student:
|
Gugatan ini meminta ganti rugi $22,000 untuk setiap pelanggan AT&T selain dendan hukuman.
| 6
|
NIv2
|
task1115_alt_ja_id_translation
|
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 have given an input which is user's command or question, based on that you have to return what will be Agent's response/reply for that particular user's command or question
what is the weather tommrow
Output:
|
It will be clear with a high of 0.00 °F and a low of 0.00 °F in Tok.
| 1
|
NIv2
|
task1603_smcalflow_sentence_generation
|
zs_opt
|
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] |
Detailed Instructions: In this task, you are given two phrases: 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 The Tail is the intention of the PersonX from the Head or not. The intention is the likely intent or desire of PersonX behind the execution of an event. For example, given the Head PersonX gives PersonY gifts, an intention might be that PersonX wanted to be thoughtful. 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.
See one example below:
Problem: Head: PersonX plays a song<sep>Tail: to hear music.
Solution: Yes
Explanation: This is a good example. PersonX plays a song because PersonX wanted to hear music.
Problem: Head: PersonX affords every ___<sep>Tail: gets thanked by other
Solution:
|
No
| 4
|
NIv2
|
task1201_atomic_classification_xintent
|
fs_opt
|
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] |
Given a real-life anecdote of a complex ethical situation, identify who is wrong here. Classify each post into the following categories : AUTHOR (if the author of the post is wrong in the situation), OTHER (if any of the others mentioned in the paragraph is wrong), EVERYBODY (if everyone mentioned is wrong) and NOBODY (if no one is wrong in the situation).
One example is below.
Q: Pretty much was hanging out with two friends. I was watching the Lakers game. They won at the very last minute and I immediately hopped up and celebrated. Before I could even finish celebrating one friend started going on about how the Lakers suck. It just pissed me off so much I screamed at her to get out my room until she left.
She knows I'm a huge fan and she likes them too. She was only saying it to antagonize me. Am I the dick here?
A: AUTHOR
Rationale: It is very rude to shout at someone and ask her to leave the room even if her comments may have antagonized the author. Hence author is at fault here.
Q: My mom and I have not been getting along the past year and a half. She was a really shitty mom but got a little better over the years.
Last year we had a big falling out because she talks so much shit about everyone and I ended up hearing all the shit she talks about me. We havent seen each other much since then but have talked and it has been going good.
So my ex boyfriend and I had a really big fight on Friday and I ended up telling her about it. Right now we are currently broken up, but have talked but not made up and he hasnt come home since Friday night. I told her about it thinking for some reason she wouldnt tell anyone. She ended up telling her bf, my aunt, and one of my brothers that I know for sure. Probably my other brother and who ever else she talks to.
Well I learned my lesson as yesterday I went over to my aunts and was going to tell her a story about Friday, but not about the fight. I started the story by saying me and EX did this activity on Friday and she said I already heard. My story wasnt about the fight but she must have thought I was going to say that. So I was annoyed last night after leaving. I left it be. Today I text my mom and say so who did you tell about my and EXs fight? She says "just your brother". I said "aunt knows to does older brother know" she said "aunts nosey, probably not brother he hasnt said anything" long story short I said "i told you that thinking you werent going to tell everyone" she says "i am done with this conversation" so i said im not going to Christmas. And Ill just have her bf drop them off when he goes.
She said thats fine she isnt doing Christmas anyways and that my aunt was. I said good good. She said keep the gifts. I said alrighty bye.
I will be sending the gifts because the gifts were for my cousins and aunt and brothers and grandma and I want them to have them. They did nothing to me. She wont be there actual Christmas day so I am maybe going over there then and seeing my grandma who is in bad shape. I texted aunt and let her know i wasnt going. She asked why i just said because of my mom but didnt go into detail. I also told my older brother who is coming up from 3 hours away and told him the same thing, said i didnt want to discuss the fight any further. He said "life is to short for you and mom to be petty. You only get 50 Christmas celebtrations and your wasting them." Then something about me and her being childish.
Am I the asshole? I should not have told her but I was really upset and wanted someone to talk to. Im just so annoyed my mom and I cant talk about anything or it gets spread throughout my entire family.
A:
|
OTHER
| 9
|
NIv2
|
task498_scruples_anecdotes_whoiswrong_classification
|
fs_opt
|
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] |
Instructions: In this task, you are given a sentence with a missing word that can be an object, a person, and/or an action. Fill in the blank with a plausible word. Although each sentence has many correct answers, you only have to write one answer.
Input: PersonX evaluates ___ in terms
Output:
|
the grass
| 3
|
NIv2
|
task1217_atomic_answer_generation
|
zs_opt
|
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] |
Detailed Instructions: In this task, you will be shown a conversation. You need to write a question with three choices for the conversation. Your question should be answerable based on the conversation and only have one correct answer. Note that you don't need to answer your question. "W" and "M" in the conversations stand for "woman" and "man".
Problem:M: Hello, and welcome to our program "Working Abroad". Our guest this evening is a Londoner, who lives and works in Italy. Her name's Susan Hill. Susan, welcome to the program. You live in Florence, how long have you been living there? W: Since 1982. But when I went there in 1982, I planned to stay for only 6 months. M: Why did you change your mind? W: Well, I'm a designer. I design leather goods, mainly shoes, and handbags. Soon after I arrived in Florence, I got a job with one of Italy's top fashion houses, Ferregamo. So, I decided to stay. M: How lucky! Do you still work for Ferregamo? W: No, I've been a freelance designer for quite a long time now. Since 1988, in fact. M: So, does that mean you design for several different companies now? W: Yes, that's right. I've designed many fashion items for a number of Italian companies, and during the last four years, I've also been designing for the British company, Burberry's. M: What have you been designing for them? W: Mostly handbags, and small leather goods. M: Has the fashion industry in Italy changed since 1982? W: Oh, yes. It has become a lot more competitive. Because of quality of products from other countries has improved a lot. But the Italian quality and design is still world-famous. M: And do you ever think of returning to live in England? W: No, not really. Working in Italy is more interesting. I also love the Mediterranean sun and the Italian life style. M: Well, thank you for talking to us, Susan. W: It was a pleasure.
Solution:
|
Where does this talk most probably take place? (A) In a studio. (B) In a clothing store. (C) At a beach resort.
| 8
|
NIv2
|
task246_dream_question_generation
|
zs_opt
|
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] |
Definition: In this task, you're given a story (which contains five sentences only). Your task is to find all the characters which are available in the given story.
Input: Sentence1: My girlfriend and I decided to cook together Tuesday. Sentence2: We chose to make fajitas. Sentence3: It was fun and easy. Sentence4: We only got in each other's way a little. Sentence5: The food was delicious and we plan to do it again soon.
Output:
|
Girlfriend, I (myself)
| 2
|
NIv2
|
task292_storycommonsense_character_text_generation
|
zs_opt
|
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] |
In this task, you need to reverse 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 small wave is best used to learn how to surf'. Reverse all words of length '3' in the given sentence.
|
a small wave is best used to learn woh to surf
| 0
|
NIv2
|
task378_reverse_words_of_given_length
|
zs_opt
|
[
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] |
You will be given a definition of a task first, then some input of the task.
From the given sentence, extract the phrase (often noun or verb) that carries the given relationship. The generated phrase should be present in the sentence.
Given Relationship: 'occupy', Sentence: 'The " Convention of the Representatives of the State of New York " stopped there in April 1776 , when Jonathan Odell was the proprietor , on their way out of New York City when the British occupied it , and discussed General Washington 's defeat at the Battle of Long Island .'
Output:
|
occupied
| 1
|
NIv2
|
task678_ollie_actual_relationship_answer_generation
|
zs_opt
|
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] |
In this task, you're given a short article. Your job is to classify the article based on its category. Use the following classification labels, 0. World, 1. Sports, 2. Business, 3. Science or Technical. Label the text "0" if it contains information related to world. Label the text "1" if it contains information related to sports. Label the text "2" if it contains information related business. Label the text "3" if it contains science or technical related information.
--------
Question: Dell Displays New TVs, Music Players NEW YORK -- Dell took the wraps off its holiday lineup this week, showing new printers, plasma televisions, and music players that will soon be available through its Web site.
Answer: 3
Question: Falcons keep heat on Bulger, RBs He #39;s a cool guy, a borderline lunatic, someone who can jam the hell out of a Strat. He #39;s got a temper that #39;s quicker than Michael Vick and spent some time last week talking football
Answer: 1
Question: News Corp adopts raft of governance changes to secure move to US SYDNEY : Global media giant News Corp caved in to investor pressure and adopted a series of corporate reforms aimed at averting a shareholder revolt over its plan to relocate from Australia to the US state of Delaware.
Answer:
|
2
| 7
|
NIv2
|
task1541_agnews_classification
|
fs_opt
|
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] |
Teacher: In this task, you need to count the number of nouns/verbs in the given sentence.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Sentence: 'A small toy kept on tray held by a man'. Count the number of nouns in this sentence.
Solution: 3
Reason: The words 'toy', 'tray', and 'man' are nouns in this sentence. So, the answer is 3.
Now, solve this instance: Sentence: 'A clock tower and another red and white building but have graffiti'. Count the number of nouns in this sentence.
Student:
|
4
| 2
|
NIv2
|
task155_count_nouns_verbs
|
fs_opt
|
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] |
Definition: You are given a sentence in English. Your job is to translate the English sentence into Italian.
Input: So young people today have lots of experience and lots of familiarity with interacting with new technologies, but a lot less so of creating with new technologies and expressing themselves with new technologies.
Output:
|
Al giorno d'oggi i giovani hanno molta esperienza e molta familiarità ad interagire con le nuove tecnologie, ma non a creare usando nuove tecnologie e ad esprimersi attraverso le nuove tecnologie.
| 2
|
NIv2
|
task1091_ted_translation_en_it
|
zs_opt
|
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] |
Teacher:You are given a math word problem and you are supposed to make use of mathematical concepts like probability, combinatorics, linear equations, sequences/series, or simple operators like addition, subtraction, division, or multiplication to answer the given question. Choose the best option from the 5 given options and report that option.
Teacher: Now, understand the problem? Solve this instance: Question: The average expenditure of a labourer for 6 months was 90 and he fell into debt. In the next 4 months by reducing his monthly expenses to 60 he not only cleared off his debt but also saved 30. His monthly income i
Option A: 70
Option B: 72
Option C: 75
Option D: 78
Option E: 81
Student:
|
Option E
| 6
|
NIv2
|
task750_aqua_multiple_choice_answering
|
zs_opt
|
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] |
TASK DEFINITION: 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.
PROBLEM: The development of high-throughput DNA sequencing technologies has enabled large-scale characterization of functional antibody repertoires, a new method of understanding protective and pathogenic immune responses. Important parameters to consider when sequencing antibody repertoires include the methodology, the B-cell population and clinical characteristics of the individuals analysed, and the bioinformatic analysis. Although focused sequencing of immunoglobulin heavy chains or complement determining regions can be utilized to monitor particular immune responses and B-cell malignancies, high-fidelity analysis of the full-length paired heavy and light chains expressed by individual B cells is critical for characterizing functional antibody repertoires. Bioinformatic identification of clonal antibody families and recombinant expression of representative members produces recombinant antibodies that can be used to identify the antigen targets of functional immune responses and to investigate the mechanisms of their protective or pathogenic functions. Integrated analysis of coexpressed functional genes provides the potential to further pinpoint the most important antibodies and clonal families generated during an immune response. Sequencing antibody repertoires is transforming our understanding of immune responses to autoimmunity, vaccination, infection and cancer. We anticipate that antibody repertoire sequencing will provide next-generation biomarkers, diagnostic tools and therapeutic antibodies for a spectrum of diseases, including rheumatic diseases.
SOLUTION: Sequencing the functional antibody repertoire-diagnostic and therapeutic discovery
PROBLEM: Background. The severe acute respiratory syndrome (SARS) epidemic that occurred in Hong Kong in 2003 caused serious public health consequences. Its impacts on health-seeking behaviors of the general public have not been assessed. Methods. Two cross-sectional, random telephone surveys interviewed 1603 Hong Kong adult residents in the post-SARS epidemic period, June and September 2003 to investigate changes in the post-SARS period. Results. Noteworthy percentages of the respondents self-reported increased frequencies of practicing favorable health-seeking behaviors in June 2003, as compared with the pre-SARS period. Few respondents reported the opposite. This was observed in different dimensions: health services seeking, adoption of healthier lifestyle, spending more resources on health, adoption of good personal hygiene, mask use when ill with influenza, and avoidance of risk behaviors. The frequencies of practicing most of these health-seeking behaviors, as measured in June and September 2003, were comparable. Further increases in healthy diet and weight control, etc., were observed during that period. Those who worried about contracting SARS were more likely to have improved health-seeking behaviors. Conclusions. The community in Hong Kong responded to the SARS epidemic by practicing more favorable health-seeking behaviors. Public health workers should utilize these opportunities to foster favorable changes. D
SOLUTION: Impacts of SARS on health-seeking behaviors in general population in Hong Kong
PROBLEM: Liver diseases are one of the fatal syndromes due to the vital role of the liver. Most of the effective treatment of liver conditions are of natural origin. Silymarin (SI) is the standard drug used for treatment of impaired liver functions. Two natural compounds possessing promising liver protection and with different chemical structures namely; the bioflavonoid hinokiflavone (HF) isolated from Junipers phoenicea family Cupressaceae and the sweet saponin Glycyrrhizin (GL) present in Glycyrrhiza glabra (liquorice) were selected for the current study. Since the two compounds are of different nature, they may act by different mechanisms and express synergistic effect. Combination of the two compounds using to dose levels were challenged with single doses of HF, GL and SI as well. The comparison was monitored via measuring serum biochemical parameters including, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma glutamyltranspeptidase (GGT), alkaline phosphatase (ALP) and total bilirubin, tissue parameters such as MDA, NP-SH and TP, histopathological study using light and electron microscope. Protective effect on kidney was also monitored histopathologically and biochemically through observing the levels of LDH, creatinine, creatinine-kinase, urea and uric acid. The combinations of HF and GL showed protective effect more than the used single doses of HF and GL alone. However, SI was superior to the used combination in the two used doses in all the measured parameters. The liver and kidney cells appearance under normal and electron microscope showed that SI treated groups showed almost normal cells with slight toxic signs. Cells from group treated with the higher doses of the combination of HF and GL showed slight signs of intoxication under light and electron microscope indicating good level of protection. Although the combination of HF and GL expressed good protection in the higher dose, however, the combination did not exceed the protective effect of SI.
SOLUTION:
|
Evaluation of the hepatoprotective effect of combination between hinokiflavone and Glycyrrhizin against CCl 4 induced toxicity in rats
| 8
|
NIv2
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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 two phrases: 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 the Head happens before the Tail or not. 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 swims at the local pool<sep>Tail: PersonX learns a new way of swimming
Output: Yes
This is a good example. The Head happens before the Tail.
New input case for you: Head: PersonX acts strange<sep>Tail: to get away
Output:
|
No
| 1
|
NIv2
|
task1206_atomic_classification_isbefore
|
fs_opt
|
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] |
Definition: Construct a question that every answer in the list is correct and reasonable for it.
Input: jesus, god, john
Output:
|
give me a name you hear a lot in the bible.
| 2
|
NIv2
|
task821_protoqa_question_generation
|
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.
In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In translation, keep numbers as it is.
The first two were found unreliable and the prosecution case rested mainly on the evidence of the remaining five approvers .
Solution: पहले दो को अविश्वसनीय मानकर बाकी पांच मुखबिरों के आधार पर मुकदमा चलाया गया|
Why? English sentence is properly converted into Hindi sentence because the input also says that the first two were judged to be untrustworthy, thus the prosecution relied heavily on the testimony of the remaining five approvers.
New input: It is his duty to give advice to the Government of India upon legal matters and to perform such other duties of a legal character , as may from time to time be referred or assigned to him by the President and to discharge the functions conferred on him by or under this Constitution or any other law for the time being in force .
Solution:
|
उसका कर्तव्य है कि वह राष्ट्रपति द्वारा समय समय पर भेजे गए अथवा सौंपे गए विधिक विषयों पर भारत सरकार को परामर्श दे तथा विधिक प्रकृति के अन्य कर्तव्यों का निर्वाह करे और संविधान अथवा तस्समय प्रवृत्त किसी अन्य विधि द्वारा प्रदत्त कृत्यों का निर्वहन करे ।
| 0
|
NIv2
|
task425_hindienglish_corpora_en_hi_translation
|
fs_opt
|
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] |
Instructions: You are given a statement written in Oriya. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement. Output the word from the correct option .
Input: Statement: ୧୮୩୦ରେ ଏହା ବ୍ରାହ୍ମ ସମାଜ ରୁପେ ଖାତି ଲାଭ କରିଥିଲେ। ତାଙ୍କ ଚେଷ୍ଟାରେ ବେଣ୍ଟିଂ <MASK>ରୁ ସତୀଦାହ ପ୍ରଥା ଉଛେଦ କରିଥିଲେ। ଇଂରେଜୀ ଭାଷାର ପ୍ରବତ୍ତନ ପାଇଁ ମଧ୍ୟ ତାଙ୍କର ଉଦ୍ୟମ ଥିଲା ସ୍ମରଣୀୟ।ତାଙ୍କ ପ୍ରଚେଷ୍ଟାରେ କଲିକତାରେ ଇଂରେଜ ସ୍କୁଲ ବେଦାନ୍ତ କଲେଜ ଏବଂ ସିଟି କଲେଜ ଆଦି ଶିକ୍ଷାନୁଷ୍ଟାନମାନ ଗଢ଼ିଉଠିଥିଲା। ସେ ବଙ୍ଗଳାରେ ସମ୍ବାଦ କୌମୁଦୀ ନାମକ ଏକ ପତ୍ରିକାର ପ୍ରକାଶ କରିଥିଲେ। 'ମିରଟ-ଉଲ-ଅଖବାର' ନାମକ ଏକ ଉର୍ଦ୍ଦୁ ଖବରକାଗଜର ସମ୍ପାଦନାର ସେ ଦାୟିତ୍ୱ ନେଇଥିଲେ। ତେଣୁ ତାଙ୍କୁ କୁହାଗଲା ଭାରତୀୟ ସମ୍ବାଦପତ୍ରର ଜନକ।
Option A: କଲିକତା
Option B: ଫ୍ରାନସ
Option C: ପଶ୍ଚିମବଙ୍ଗ
Option D: ଭାରତ
Output:
|
ଭାରତ
| 3
|
NIv2
|
task951_wiki_cloze_or_multiple_choice_question_answering
|
zs_opt
|
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] |
Definition: You are given a sentence in Galician. Your job is to translate the Galician sentence into Hebrew.
Input: Obrigado.
Output:
|
אובריגדו.
| 2
|
NIv2
|
task1242_ted_translation_gl_he
|
zs_opt
|
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] |
Detailed Instructions: In this task, you are given inputs 'i', 'j', and A, where 'i' and 'j' are integers and A is a list. A list is shown by two brackets and comma-separated numbers and characters inside, like ['1', '12', 'l']. You need to concatenate all elements of A from the ith element to the jth element, and then reverse the resulting string. 'i' and 'j' will be non-negative, and will always have a value less than the length of A. 'i' will always be less than 'j'. Perform the operations in order, i.e., do not reverse first and then concatenate.
Q: 23, 26, ['2291', '1199', '7831', 'j', 'T', '2507', '2017', '6551', '287', 'z', '3041', '7857', 'j', '4899', 'a', '1399', '3515', '6011', '1873', 'L', '8309', '2409', 'S', '7937', '7735', '1303']
A:
|
303153777397S
| 9
|
NIv2
|
task267_concatenate_and_reverse_all_elements_from_index_i_to_j
|
zs_opt
|
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] |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Farsi.
Ex Input:
או הנכד שלי, או מה שלא יהיה.
Ex Output:
یا نوه ی من ، یا هر کودکی در پیرامون من.
Ex Input:
או להתעלות מעבר לעתיד: כלומר, החיים מתחילים אחרי המוות.
Ex Output:
یا می توانید « آینده گرای ماوراء الطبيعه » باشید: باور کنید که زندگی پس از مرگ شروع می شود.
Ex Input:
כשלמדתי איך הצלליות נעות, ביחס לשעות שחלפו ביום, הבנתי כמה זמן יעבור עד שיבואו לאסוף אותי הביתה.
Ex Output:
|
از آنجا که یاد گرفته بودم با حرکات سایه ها گذشت ساعت را بفهمم ، فهمیدم که چه مدتی طول کشید تا من برداشته و به خانه برده شوم.
| 1
|
NIv2
|
task1113_ted_translation_he_fa
|
fs_opt
|
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] |
You are given a question or fill-in-the-blank question, two answer options (Option1 and Option2) and an Explanation. Your task is to find the correct answer (return the string of the correct option, not option1/2) for the given question from the given options and using explanation.
Ex Input:
Question: When we add more water to something there will be
Option1: fewer reactions
Option2: more reactions
Explanation: More water allows more chemical reactions.
Ex Output:
more reactions
Ex Input:
Question: Joe is pulling a rubber band with his fingers. When does the band have the most elastic force?
Option1: at rest
Option2: when stretched
Explanation: The elastic force increases the more the material is stretched or compressed.
Ex Output:
when stretched
Ex Input:
Question: Jeff added more and more processors to the supercomputer. The supercomputer will now likely be _____ powerful.
Option1: more
Option2: less
Explanation: But the more computing power that goes into the model and the care with which the scientists construct the model can increase the chances that a model will be accurate.
Ex Output:
|
more
| 1
|
NIv2
|
task178_quartz_question_answering
|
fs_opt
|
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Paraphrase the given questions to have different wording. Your paraphrased questions should have the same answer as the original question. Try to change the sentence as much as possible using synonyms and/or rearranging the structure of the sentence. The questions are in three domains: presidents, national parks, and dogs. Each question has a keyword indicating its domain. Keywords are "this national park", "this dog breed", and "this president", which will be replaced with the name of an actual president, a national park, or a breed of dog. Hence, in paraphrasing, this keyword should also be used the same way. Do not write questions that compare or involve multiple domains. Do not write open-ended or subjective questions (e.g., questions that can be answered differently by different people.) Make your questions specific and concrete. Your question should have the same type of answer as the original question(e.g., if the question is extractive, the paraphrased question should be extractive as well.)
One example: Does this dog breed have short legs compared to the rest of its body?
Solution is here: Is the body of this dog breed large compared to its legs?
Explanation: The output has the same meaning and same answer as the original sentence. We changed the first sentence by rearranging the structure of the sentence.
Now, solve this: Was this president ever the governor of an east coast state?
Solution:
|
Did this president serve as an east coast state governor?
| 6
|
NIv2
|
task1562_zest_text_modification
|
fs_opt
|
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] |
In this task, you will be shown an extract from a movie plot. You need to read the extract and create questions that can be answered from the extract. The questions should be well-formed and grammatically correct. The questions should be completely answerable from the given passage and should not require any external knowledge. Subjective questions are not allowed. Create questions that result in factoid answers. A simple rule of thumb to decide whether a question is factoid or not is to see if two different people with average reading/comprehension skills would come up with the same answer after reading the passage.
As an eight-year-old boy, Allen Bauer (David Kreps) is vacationing with his family near Cape Cod. While taking a sight-seeing tour on a small boat, he gazes into the ocean and sees something below the surface that fascinates him, while his older brother Freddie Bauer is walking around the boat fascinated by the women. Allen jumps into the water, even though he cannot swim. He grasps the hands of a girl who is inexplicably under the water with him and an instant connection forms between the two. Allen can now breathe under water as he is in the hands of a mermaid. However, Allen is pulled to the surface by the deck hands and the two are separated, though apparently no one else sees the girl. After the ferry moves off, Allen looks back at the girl, who dives underwater showing her mermaid's tail. Allen comes to believe the encounter was a near-death hallucination, but his bond with the mermaid proves so strong that his subsequent relationships with women fail as he seeks the connection he felt with the mermaid.Years later, Allen (Tom Hanks) is a co-owner of a wholesale fruit and vegetable business in New York City with his womanizing older brother Freddie (John Candy). Depressed after his latest breakup, Allen returns to Cape Cod, where he encounters eccentric scientist Dr. Walter Kornbluth (Eugene Levy). After Allen is left alone when his motorboat conks out, he again falls into the sea, and is knocked out when the boat hits his head. He wakes up with a headache on a beach, where he encounters a beautiful naked woman with long blonde hair, a necklace with a lion medal, and the inability to talk (Daryl Hannah) who, unknown to him, is the mermaid he met as a boy (her tail transforms into legs when it becomes dry). After kissing him, she dives into the sea and leaves Allen to return home. Kornbluth, while diving in order to seek proof of strange sea creatures, also encounters the mermaid in her sea form, causing him to become obsessed with finding her again.The mermaid finds Allen's wallet in the water and goes to a sunken boat where she finds a map. Using Allen's wallet to find where he is from, she then decides to find him in New York. She comes ashore naked at the Statue of Liberty, where she is arrested for indecent exposure. Using information from Allen's wallet, the police contact Allen, and the mysterious girl gets released into his care. She learns how to speak English from watching television, and says her true name is a high-pitched chirp sound in the language of mermaids. She's eager to see a big city for the first time in her life, and when Allen suggests a more audible name, she selects Madison from a Madison Avenue sign. She tells Allen that she will be in New York for "six fun-filled days when the moon is full" and if she stays longer, she can never go home again (the reason for this is unexplained). Despite Madison's occasional unusual behavior - such as locking herself in the bathroom to enjoy a bath in her mermaid state, wildly gobbling up a lobster dish in a posh restaurant, and having a large mermaid fountain brought into his apartment - she and Allen fall in love. Allen proposes to Madison, but she declines and runs away. After pondering her reason for coming to the city in the first place, Madison returns to Allen and agrees to marry him, with the added promise of telling him the truth about herself at an upcoming dignitary dinner to welcome the President of the United States.Meanwhile, Kornbluth, realizing that the naked woman at Liberty Island was the mermaid he had encountered, pursues the couple trying to expose her as a mermaid by splashing her with water. Many attempts are unsuccessful, and Kornbluth ends up with multiple injuries including a badly broken arm and whiplash. Kornbluth finally lies in wait with water tanks at the dignitary dinner, splashing Madison with an attached hose and successfully proving the existence of mermaids when government officials are surprised to see Madison's tail flapping in public. Madison is seized by government agents and put under government study, headed by Kornbluth's rival Dr. Ross (Richard B. Shull) for examination. However, Kornbluth regrets his actions after he learns that Madison is due to be studied and dissected, as he just wanted to prove that he wasn't crazy.Allen is shocked by Madison's secret and when he voices out his disillusionment to his brother, Freddie lashes out at him, telling his brother how unbelievably happy he was with her. Realizing he still loves Madison, Allen tries to make contact with government officials to let him see Madison, but to no avail. He then confronts a guilt-ridden Kornbluth, who agrees to help him rescue her.Impersonating Swedish scientists, Freddie and Allen enter the lab with Kornbluth and smuggle Madison outside. Despite being under hot pursuit by United States troops, Allen and Madison make it back to the docks at the New York harbor and she tells Allen that he can survive under water as long as he is with her. Allen realizes she was the young mermaid he had met so long before. The United States military arrive to recapture her, ignoring Allen's demands to let her be free. Although Madison warns him that if he comes to live in the sea he can't return, he jumps into the water after her and they elude their pursuers. Together they swim along the ocean floor toward what appears to be an underwater kingdom.
|
Who is shocked by Madison's secret?
| 0
|
NIv2
|
task193_duorc_question_generation
|
zs_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.
One example is below.
Q: អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃពីធីប្រកួតពានរង្វាន់ពិភពលោកនៃកីឡាបាល់ឱបឆ្នាំ2007ដែលប្រព្រឹត្តនៅប៉ាសឌេសប្រីន ក្រុងប៉ារីស បារាំង។
A: フランスのパリ、パルク・デ・プランスで行われた2007年ラグビーワールドカップのプールCで、イタリアは31対5でポルトガルを下した。
Rationale: The Khamer sentence is correctly converted into Japanese because the converted sentence holds the message that Italy defeated Portugal 31–5 in Pool C of the 2007 Rugby World Cup at the Parc des Princes in Paris, France. Also, translated sentence preserves the numbers as it is.
Q: អតីតប្រធានក្រុមហ៊ុនអន្តរជាតិទីកូ លោកដេនីសកូស្លូស្គី ក៏ដូចជាប្រធានផ្នែកហិរញ្ញវត្ថុលោកម៉ាកស្វតត្រូវបានចោទប្រកាន់ថាបានយកប្រាក់ចំនួនច្រើនជាង600លានដុល្លាររបស់ក្រុមហ៊ុន។
A:
|
前タイコインターナショナル社の最高経営責任者デニス・コズロースキーおよびマーク・シュワルツ最高財務責任者らが共に、会社から60億ドル以上を横領した罪に問われている。
| 9
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NIv2
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task1122_alt_khm_ja_translation
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fs_opt
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] |
Teacher:In this task, you will be shown a short story with a beginning, two potential middles, and an ending. Your job is to choose the middle statement that makes the story coherent / plausible by writing "1" or "2" in the output. If both sentences are plausible, pick the one that makes most sense.
Teacher: Now, understand the problem? Solve this instance: Beginning: It had long been tradition to hunt whales during the Spring. Middle 1: Tommy and Brad hunted the whales. Middle 2: Tommy and Brad saw the whales. Ending: Eventually they were arrested and moderately fined.
Student:
|
1
| 6
|
NIv2
|
task069_abductivenli_classification
|
zs_opt
|
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] |
In this task, you are given a sentence from the research paper and your task is to classify the given sentence into the following categories: Background (Why is this problem important? What relevant works have been created before? What is still missing in the previous works? What are the high-level research questions? How might this help other research or researchers?), Purpose (What specific things do the researchers want to do? What specific knowledge do the researchers want to gain? What specific hypothesis do the researchers want to test?), Method (How did the researchers do the work or find what they sought? What are the procedures and steps of the research?), or Finding (What did the researchers find out? Did the proposed methods work? Did the thing behave as the researchers expected?).
synthetic , DNA vaccine targeting the pre-membrane + envelope proteins ( prME ) of ZIKV.
|
purpose
| 0
|
NIv2
|
task1163_coda19_section_classification
|
zs_opt
|
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] |
In this task, you will be presented with a question, and you have to write the part-of-speech tag for each word in the question. Here is the Alphabetical list of part-of-speech tags used in this task: CC: Coordinating conjunction, CD: Cardinal number, DT: Determiner, EX: Existential there, FW: Foreign word, IN: Preposition or subordinating conjunction, JJ: Adjective, JJR: Adjective, comparative, JJS: Adjective, superlative, LS: List item marker, MD: Modal, NN: Noun, singular or mass, NNS: Noun, plural, NNP: Proper noun, singular, NNPS: Proper noun, plural, PDT: Predeterminer, POS: Possessive ending, PRP: Personal pronoun, PRP$: Possessive pronoun, RB: Adverb, RBR: Adverb, comparative, RBS: Adverb, superlative, RP: Particle, SYM: Symbol, TO: to, UH: Interjection, VB: Verb, base form, VBD: Verb, past tense, VBG: Verb, gerund or present participle, VBN: Verb, past participle, VBP: Verb, non-3rd person singular present, VBZ: Verb, 3rd person singular present, WDT: Wh-determiner, WP: Wh-pronoun, WP$: Possessive wh-pronoun, WRB: Wh-adverb
Example input: Who were the builders of the mosque in Herat with fire temples ?
Example output: WP VBD DT NNS IN DT NN IN NNP IN NN NNS .
Example explanation: This is a good example. All of the POS tags are correct.
Q: What is the Event/Location whose species whose ideal bait are Bloodworms ?
A:
|
WP VBZ DT NNP WP$ NNS WP$ JJ NN VBP NNP .
| 3
|
NIv2
|
task345_hybridqa_answer_generation
|
fs_opt
|
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-0.3641442358493805,
-0.09231974929571152,
0.7821656465530396,
-0.4718056321144104,
0.02527349442243576,
-0.3199523687362671,
-0.3882366120815277,
-0.0732894167304039,
0.791528582572937,
-0.3358120918273926,
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0.45773738622665405,
0.09443134069442749,
-0.34623610973358154,
0.21939855813980103
] |
TASK DEFINITION: You are given a sentence in Polish. Your job is to translate the Polish sentence into Hebrew.
PROBLEM: Nie zawsze jednak tak było.
SOLUTION: אבל זה לא היה כך תמיד.
PROBLEM: To działa dopóki polegamy na właściwych ludziach.
SOLUTION: כלומר, זה עובד כל עוד זה נועד לתקן אחרים.
PROBLEM: Wśród polityków?
SOLUTION:
|
האם היא שם עם הפוליטיקאים?
| 8
|
NIv2
|
task1260_ted_translation_pl_he
|
fs_opt
|
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] |
Detailed Instructions: Given a text passage, come up with an appropriate title for it. The title should accurately represent what the main focus of the passage is. The title of a passage may be present in the first few sentences of the passage and/or be referred to multiple times in the passage. The title should be 1-5 words long.
Q: The Origination Clause , sometimes called the Revenue Clause , is part of the United States Constitution . This clause says that all bills for raising revenue must start in the House of Representatives , but the Senate may propose or concur with amendments as in the case of other bills .
A:
|
Origination Clause
| 9
|
NIv2
|
task769_qed_summarization
|
zs_opt
|
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] |
Detailed Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into English.
Problem:دعونا نقول أنّني صياد ومزارع.
Solution:
|
Let's say I'm a fisherman and a farmer.
| 8
|
NIv2
|
task1230_ted_translation_ar_en
|
zs_opt
|
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] |
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.
Kimberley had cured herself.
|
good
| 0
|
NIv2
|
task1560_blimp_binary_classification
|
zs_opt
|
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] |
Instructions: In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In the translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
Input: दुर्भाग्य से , अटल बिहारी वाजपेयी की कमजोर सरकार के कारण राजनीतिकों ने इस खेल में खुद को औजार के रूप में इस्तेमाल होने दिया है और मंत्रियों ने भी ' ओस सबूतों ' की तरह के बयान दिए हैं ।
Output:
|
Unfortunately , because Atal Bihari Vajpayee runs a weak government , politicians have allowed themselves to be used as tools in the game and ministers have also made statements of the “ clinching evidence ” kind .
| 3
|
NIv2
|
task424_hindienglish_corpora_hi_en_translation
|
zs_opt
|
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] |
Instructions: You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Input: Pensateci come un microscopico numero di vecchi economisti e ideologisti non rappresentativi che si sono appropriati del processo.
Output:
|
妥協できないのはごく少数時代遅れの経済学者と偏った狂信家です
| 3
|
NIv2
|
task1248_ted_translation_it_ja
|
zs_opt
|
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] |
A piece of text from one of these 5 languages - French, English, Dutch, Somali, Tagalog is given. Generate the language to which the text belongs.
One example: Text: Cheval de soins pour les enfants de 3 ans!
Solution is here: French
Explanation: The given text is in French language
Now, solve this: Text: 29 iyo malab, iyo subag, iyo ido, iyo faar lo'aad, oo waxay waxaas oo dhan u keeneen Daa'uud iyo dadkii la socday inay cunaan, waayo, waxay isyidhaahdeen, Dadku cidladay ku gaajoodeen, oo ku daaleen, oo ku harraadeen.
Solution:
|
Somali
| 6
|
NIv2
|
task447_opus_paracrawl_classification
|
fs_opt
|
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] |
Definition: 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".
Input: Event:PersonX makes a lot of noise. Intent: 1) to help persony 2) to be nice 3) to utilize their skills
Output:
|
Negative
| 2
|
NIv2
|
task923_event2mind_classifier
|
zs_opt
|
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] |
In this task, you are given dvd product reviews in French language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Q: Un grand spectacle !! . La guerre de Troie revisitée par Wolfgang Petersen, c'est un scénario béton, des acteurs fantastiques (avec, notamment, un Brad Pitt particulièrement charismatique en Achille), une mise en scène très spectaculaire et des dialogues remarquables. Les scènes de bataille sont impressionnantes, les personnages ont de l'épaisseur, la musique souligne l'aspect grandiose de l'ensemble, ce film de 2h35 se révèle passionnant et même trop court, tant on adhère à l'histoire ! Le dvd du film nous propose une image et un son de tout premier ordre et le dvd bonus, même s'il est trop court, est de grande qualité et va à l'essentiel.
A:
|
POS
| 4
|
NIv2
|
task483_cls_french_dvd_classification
|
zs_opt
|
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] |
Detailed Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Polish.
Problem:في عام 1968 خطر ببالي ان اضع قاعة للموسيقى في الجهة الشمالية للمبنى اثناء بناءه.
Solution:
|
W 1986 zachowałem wystarczająco przytomny umysł, by zbudować salę koncertową w północnej części tego budynku, gdy jeszcze go budowałem.
| 8
|
NIv2
|
task1107_ted_translation_ar_pl
|
zs_opt
|
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] |
Detailed Instructions: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Farsi.
Q: 僕は現代美術が大好きですがこの世界とこの環境に強く不満を感じることがよくあります
A:
|
من عاشق هنر معاصر هستم اما گاهی اوقات ، از هنر معاصر دنیا و نمایش هنر معاصر خسته میشم.
| 9
|
NIv2
|
task1098_ted_translation_ja_fa
|
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 are given a question and a context passage. You have to answer the question based on the given passage.
What was the main issue for the ROK forces?, Context: In contrast, the ROK Army defenders were relatively unprepared and ill-equipped. In South to the Naktong, North to the Yalu (1961), R.E. Appleman reports the ROK forces' low combat readiness as of 25 June 1950. The ROK Army had 98,000 soldiers (65,000 combat, 33,000 support), no tanks (they had been requested from the U.S. military, but requests were denied), and a 22-piece air force comprising 12 liaison-type and 10 AT6 advanced-trainer airplanes. There were no large foreign military garrisons in Korea at the time of the invasion, but there were large U.S. garrisons and air forces in Japan.
Output:
|
unprepared and ill-equipped
| 1
|
NIv2
|
task1295_adversarial_qa_question_answering
|
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.
In this task, you are given a sentence in English, and your task is to translate it into Persian.
not just the words . and thats where a great film editor can help a director .
Solution: فقط کلمات نيستن؛ يک تدوينگر خوب خيلي به کار گردان کمک ميکنه .
Why? This is a good example. The above sentence is correctly translated from English to Persian.
New input: im sure it does .
Solution:
|
مطمئنم که اينکارو ميکنه .
| 0
|
NIv2
|
task658_tep_en_fa_translation
|
fs_opt
|
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] |
TASK DEFINITION: Given a premise, an initial context, an original ending, and a counterfactual context, the task is to generate a new story ending aligned with the counterfactual context and as close to the original ending as possible. Each instance consists of a five-sentence story. The premise is the first sentence of a story, and the second sentence, which is the initial context, provides more information about the story's context and the story's general plot. The original ending is the last three sentences of the story. Also, a counterfactual context is a slight modification to the initial context. You should write a new story ending that edits the original story ending as little as possible to regain coherence with the counterfactual context. To sum up, you should write the last three sentences of a story based on the premise(first sentence) and the counterfactual context(second sentence) of the story.
PROBLEM: Premise: Carly loved to collect antique bottles.
Initial Context: She went to a garage sale and saw a very unique and old wine bottle.
Original Ending: As she was about to make an offer another woman inquired about it too. Carly began a bidding war over a bottle that was originally 50 cents. In the end she won with the highest bid of 172 cents.
Counterfactual Context: She went to a garage sale and bought one.
SOLUTION: As she was about to make an offer on another bottle, another woman inquired about it too. Carly began a bidding war over a bottle that was originally 50 cents. In the end she won with the highest bid of 172 cents.
PROBLEM: Premise: Allison was getting some wine out of the fridge.
Initial Context: As she took it out, the glass immediately fell.
Original Ending: When the glass shattered, wine spilled all over. Allison sighed. She had to clean it up quickly.
Counterfactual Context: She took it out and poured some into a plastic cup.
SOLUTION: She accidentally tipped the plastic cup over, wine spilled all over. Allison sighed. She had to clean it up quickly.
PROBLEM: Premise: Joe stopped at a traffic light.
Initial Context: The light was green but he didn't go.
Original Ending: The people behind him honked their horns. They were getting frustrated, but Joe didn't budge. He said that it was a beautiful day, and he was going to enjoy it.
Counterfactual Context: The light stayed red.
SOLUTION:
|
The people behind him honked their horns impatiently. They were getting frustrated, but Joe wouldn't go on a red light. He said that it was faulty, but it wasn't worth getting a ticket for.
| 8
|
NIv2
|
task269_csrg_counterfactual_story_generation
|
fs_opt
|
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] |
Given the task definition and input, reply with output. You are given a sentence in Galician. Your job is to translate the Galician sentence into Farsi.
Aquel día cambiou a mińa práctica clínica e, en última instancia, a mińa carreira.
|
اون روز شیوه طبابت من و در نهایت زندگی حرفهای من را تغییر داد.
| 5
|
NIv2
|
task1245_ted_translation_gl_fa
|
zs_opt
|
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] |
Given the task definition and input, reply with output. This task is about writing a correct answer for the reading comprehension task. Based on the information provided in a given passage, you should identify the shortest continuous text span from the passage that serves as an answer to the given question. Avoid answers that are incorrect or provides incomplete justification for the question.
Passage: The etymology of the name is uncertain. The spelling Ἀπόλλων (pronounced [a.pól.lɔːn] in Classical Attic) had almost superseded all other forms by the beginning of the common era, but the Doric form Apellon (Ἀπέλλων), is more archaic, derived from an earlier *Ἀπέλjων. It probably is a cognate to the Doric month Apellaios (Ἀπελλαῖος), and the offerings apellaia (ἀπελλαῖα) at the initiation of the young men during the family-festival apellai (ἀπέλλαι). According to some scholars the words are derived from the Doric word apella (ἀπέλλα), which originally meant "wall," "fence for animals" and later "assembly within the limits of the square." Apella (Ἀπέλλα) is the name of the popular assembly in Sparta, corresponding to the ecclesia (ἐκκλησία). R. S. P. Beekes rejected the connection of the theonym with the noun apellai and suggested a Pre-Greek proto-form *Apalyun. Question: Apellon is derived from what Doric month?
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Apellaios
| 5
|
NIv2
|
task075_squad1.1_answer_generation
|
zs_opt
|
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Q: We would like you to classify each of the following sets of argument pairs (discussing Gay Marriage) into either SIMILAR or NOT SIMILAR. A pair of arguments is considered SIMILAR if the arguments are about the same FACET (making the same argument), and is considered NOT SIMILAR if they do not have the same FACET. A FACET is a low level issue that often reoccurs in many arguments in support of the author's stance or in attacking the other author's position.
Sent1: Let me re-explain myself: If we legalize same-sex marriage, everyone will have an equal right to bestow their marriage benefits on one other person that they fall in love with.
Sent2: I think they are now advocating everyone to be allowed to get all marriage benefits even if they have no desire to be married because they are concerned about being inclusive to all.
A:
|
Not similar
| 7
|
NIv2
|
task147_afs_argument_similarity_gay_marriage
|
zs_opt
|
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] |
Detailed Instructions: In this task, you are given inputs i,j, and A, where i and j are integers and A is a list. You need to return the sum of all the numerical elements in the list A between the positions i and j (including positions i and j). Return 0 if no numerical element is present in the list between the given ranges. i and j will be non-negative, and will always have a value less than the length of A. i will always be less than j.
Problem:9, 16, ['3787', '5195', '7117', '709', 'k', '8279', '5461', '985', 'Y', 'Z', 'Q', '2921', 'x', '6917', '7953', '5289', 'l', '2669', '3349', '1035', '8793', '8879']
Solution:
|
23080
| 8
|
NIv2
|
task606_sum_of_all_numbers_in_list_between_positions_i_and_j
|
zs_opt
|
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] |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Japanese.
One example is below.
Q: מה מייחד את המוח האנושי?
A: 人の脳の何がそんなに特別なのでしょうか ？
Rationale: The Hebrew sentence is correctly translated into Japanese. They both refer to the human brain.
Q: ואז תפרו אותי. לקח להם שעה שלמה לתפור אותי מחדש.
A:
|
その後体の縫合に1時間かかりました
| 9
|
NIv2
|
task1235_ted_translation_he_ja
|
fs_opt
|
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] |
This task is to translate the Telugu Language Input to English Language Output
Q: మాకు ఇమెయిల్ పంపండి info@anatod.com
A:
|
FTTx - Wireless
| 4
|
NIv2
|
task1617_cc_alligned_translate_tel_eng
|
zs_opt
|
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] |
In this task, you're given a statement and three sentences as choices. Your job is to determine which sentence can be inferred from the statement. Incorrect choices change the meaning in important ways or have details that are not mentioned in the statement. Indicate your answer as 1,2, or 3 corresponding to the choice number of the selected sentence.
One example: Statement: Next to the MGM Grand you will find M and M World, four stories of merchandise and memorabilia dedicated to the candy that doesn't melt in your hand. Choices: 1. The candy has many fans who love its attractions. 2. There's four stories of memorabilia dedicated to a candy. 3. That particular candy melts and becomes difficult to eat.
Solution is here: 2
Explanation: The candy may or may not be popular, and does not melt and become difficult to eat. Hence the second choice is the only one that fully agrees with the statement.
Now, solve this: Statement: Blacks and whites began to meet and date, especially on college campuses, which started admitting African-Americans in larger numbers in the '60s and '70s. Choices: 1. It was common to see a white man dating a black woman. 2. Colleges started to let more African-Americans in which resulted in more integrated dating. 3. Asian men began dating white women more often.
Solution:
|
2
| 6
|
NIv2
|
task200_mnli_entailment_classification
|
fs_opt
|
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] |
Detailed Instructions: In this task you are given a list of numbers and you need to find the average of each two consecutive values. The average of two numbers a and b is calculated as: (a + b) /2. The output should be a list of the averages of each two consecutive values. A list is presented with two brackets and comma-separated values, like: [1,2,3].
Problem:[86, -46, 0, 78, 5, 96]
Solution:
|
[20.0, -23.0, 39.0, 41.5, 50.5]
| 8
|
NIv2
|
task124_conala_pair_averages
|
zs_opt
|
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] |
instruction:
In this task, you're given a context, a sentence, and a character. The sentence describes an action or job of the given character. Also, the context provides more information about the sentence or the character. Your task is to write the character's motivation by doing a specific job, which is given in the sentence. You can use context to find the motivation; however, all the inputs do not provide context. Also, in some inputs, there can be zero motivation; output, 'None' in this case.
question:
Context: None
Sentence: The Smith family went to the same beach every summer.
Character: Children
answer:
None
question:
Context: Evan and Alex were excited for field day at school.
Sentence: They were going to be on different teams.
Character: Blue team
answer:
None
question:
Context: I had been dating a beautiful lady for six years. I wanted to marry her. I bought a ring. I got down on one knee and asked her to be my wife.
Sentence: She agreed to get married.
Character: I (myself)
answer:
|
None
| 9
|
NIv2
|
task294_storycommonsense_motiv_text_generation
|
fs_opt
|
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] |
Teacher:You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Italian.
Teacher: Now, understand the problem? Solve this instance: ستيف جيرفيتسن: هاهي ، فوق أحد الأكواب
Student:
|
SJ: Sei sopra un bicchiere.
| 6
|
NIv2
|
task1106_ted_translation_ar_it
|
zs_opt
|
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] |
Teacher:In this task you will be given a list of numbers. A list is shown by two brackets and comma-separated numbers inside, like: [1,2,3]. You should remove all of the even numbers from the list. If every number in the input list is even an empty list should be returned. Zero should be counted as an even number.
Teacher: Now, understand the problem? Solve this instance: [35, 181, 26, 10, 183, 82, 177]
Student:
|
[35, 181, 183, 177]
| 6
|
NIv2
|
task205_remove_even_elements
|
zs_opt
|
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] |
Teacher:In this task, you're given the beginning and the middle of a three-part story. Your job is to complete the short story by writing a probable ending. 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 ending, and use names instead of pronouns (e.g. he / she) wherever possible.
Teacher: Now, understand the problem? Solve this instance: Beginning: Bob's high school spirit week required him to wear a color. Middle: Bob thought that the student council should provide colored cloth for the kids who couldn't afford clothes in those colors.
Student:
|
Bob earned double points for his team with this great idea!
| 6
|
NIv2
|
task071_abductivenli_answer_generation
|
zs_opt
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Given a real-life anecdote of a complex ethical situation, generate a suitable title that describes the main event/root cause of the situation. Imagine that the given text is a social media post, and you have to write the title of the post, so the users can decide to read the main text or not.
We recently visited family for Christmas, and everything was fine except my niece caught the flu a few days before Christmas. Her parents still came around, and sister in law insisted on holding my child. I did not want that, but was told to "not worry" and that "shes too small to get the flu".
So the SIL still held the baby. Now we are back home and my wife has the flu. I am worried that my baby girl will get very sick. I have heard the flu can be deadly to children. Naturally I am extremely pissed at this point. In our family group chat, my wife informs the group she has the flu. SIL tells us this flu is the worst and to quarantine my wife. I say "Thanks for letting us know. Would have been nice not to have been exposed. We will manage. But, I am kinda low on PTO, so."
Ensue chaos. Everyone is pissed at me, including my wife. My other SIL said, it's not like they got sick on purpose, and I think to myself, "They could have chosen to stay home and not spread the flu, on purpose..."
Apparently potentially infecting a baby with the flu isn't as bad as sending a frustrated text. AITA?
being frustrated at family member exposing my 3 month child to the flu
Try to keep it short. My mum is normally a really love, kind and caring person but as she is hitting menopause is getting a bit funny. Have I been too sensitive in this situation and acted like an asshole? If my brother sees this he will know its from me so hi!
Im currently having a miscarriage. I was at my parents the other day and my mum kept talking about a holiday we are going on all together (siblings, my hubby and children etc). She is always wanting to get her next holiday fix. Anyway I was trying to be positive and not a debbie downer as that very morning my hubby and I had been told our babys heart beat had stopped and it was a matter of a waiting game.
In my group chat with my mum and siblings I informed my two brothers of the sad news and they offered their condolences. My mum immediately followed up with a comment that said, 'Great news guys I was able to get that holiday house in blah blah blah!!' I felt that was an incredibly insensitive thing to follow up on my miscarriage news. She also continued to keep talking to me about it even though I kept telling her I might not even be able to make it as I might need a D&C if my body hadn't miscarried by then. She blew up at me for being rude or something I don't know I was too pissed off at this time and commented on how I hadn't even seemed that upset. Keep in mind she had suffered miscarriages so should be quite aware of how I felt and that I wasn't exactly in a happy mood wanting to talk about holidays etc. She said I take it for granted that she watches my kids (she does watch my kids...but maybe a total of 10 times in the whole year and 2 nights in this whole year). I told her I do appreciate it and I was not really in a mood to talk about holidays as I was trying to keep it together in front of my other kids.
AITA in this situation and too sensitive?
feeling my mum was insensitive
I feel like this is a two part question.
I am a coordinator/ scheduler for a service based company. We have four divisions. I cover one, 'L' covers another, and our Boss 'C' covers two. We each have a supervisor for our department that we work closely with and act a bit like their secretary. So we technically have two bosses.
Us three coordinators do a pretty good job of covering for each other.
I woke up today feeling sick. I was shivering but sweating, with muscle aches. I would have called out sick. However, 'C' has been out on vacation for a week and comes back tomorrow. Monday mornings are crucial because it's when we all send out calls and go over what came in over the weekend. I did not want to just throw 'L' to the wolves so I went in. I told everyone to not get close to me. I covered my mouth when speaking. I told everyone I was just in for an hour so I could get everything lined up in a way 'L' could easily take over. Everyone told me to stay the hell away, thanks for being a trooper, but go home asap.
I called my supervisor and told him my plans. He asked me to tough it out and stay until noon.
I was pretty upset and mentioned it to 'L' that I would be staying because my boss didn't think she could cover all the divisions, even though we have all done it before.
About thirty minutes later she came in and said "Please go home, just tell me what you need me to do." I called my supervisor on the way home to let him know.
Now he's upset because he asked me to stay and 'L' doesn't have the authority to send me home.
I already felt like an asshole for showing up sick, even if briefly. Now I feel like I shouldn't have showed up at all.
|
going into work sick, then leaving against my supervisors request
| 0
|
NIv2
|
task500_scruples_anecdotes_title_generation
|
fs_opt
|
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] |
In this task, you are given an input list. A list contains several comma-separated items written within brackets. You need to collate all the alphabetical elements at the start of the list followed by all the numerical elements of the list. Maintain the order in which the alphabetical elements appear in the given input list, and do the same for the numerical elements.
['L', '1391', 'U', 'R', '6747', 'T', 'i', 'x', '1521', '9807', 'A', '5371', 'h', '4647', 'Z', '9663', 'a']
|
L, U, R, T, i, x, A, h, Z, a, 1391, 6747, 1521, 9807, 5371, 4647, 9663
| 0
|
NIv2
|
task509_collate_of_all_alphabetical_and_numerical_elements_in_list_separately
|
zs_opt
|
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] |
Q: In this task, you're given an article and an answer. Your task is to generate the question for the answer based on the given article.
Article: (1)Full-time Secretary Position Available Applicants should have at least 2 year's experience and be able to type 60 words a minute.No computer skills required.Apply in person at United Business Ltd, 17 Browning Street, Leeds. (2)Part-time Job We require three part-time shop assistants to work during the evening.No experience required, applicants should be between 18 and 26 years old.Call 0115665643 for more information. (3)Computer Trained Secretaries Do you have experience working with computers? If you want to know more about us, call 0457996754. (4)Teaching Assistants Needed Hania's Playshool needs 2 young teaching assistants to help with classes from 9 to 3 pm.Applicants should have references.For more information please visit www.Haniaplayschool.com.uk. (5)Weekend Work Available We are looking for retired adults who would like to work part-time on weekends for Rubberlast Group Ltd.Duties include answering the telephone and giving customers' information.For more information call us at 0113--6741326. (6)University Positions Open The University of Bristol is looking for 4 teaching assistants to help with homework correction.Applicants should have a degree in one of the following Political Science, English, Economics or History.Please call the University of Bristol for more information. (7)Home Delivery Representative We are looking for someone who has excellent customer care, communication skills, a sales background with at least one year's experience and is a good team player with creative ideas.In return we offer a starting salary of $ 20,000 and 25 days paid holiday per year.For more information please call Direct Delivery Team of Yorkshire Post on 0113--2388318.
Answer: Teaching Assistant in the University of Bristol.
A:
|
Which position is most suitable for a retired person?
| 7
|
NIv2
|
task311_race_question_generation
|
zs_opt
|
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Detailed Instructions: A text is given in Gujarati. Translate it from the Gujarati language to the Telugu language. The translation must not omit or add information to the original sentence.
Q: એએસઆરબી પાસેથી બજેટ વડાને પણ અલગ કરવામાં આવશે અને ડીએઆરબી અંતર્ગત તેની રચના કરવામાં આવશે તેમજ સચિવાલયમાં એએસઆરબીની તેની પોતાની વહીવટી સ્ટાફની એક સ્વતંત્ર વહીવટી અંકુશ ધરાવી કેડર હશે.
A:
|
ఎఎస్ఆర్బి యొక్క బడ్జెట్ హెడ్ ను కూడా ఐసిఎఆర్ నుండి వేరు పరచి, డిఎఆర్ఇ లో భాగంగా ఏర్పాటు చేస్తారు. అలాగే, ఎఎస్ఆర్బి కి సచివాలయం లో తనకంటూ సొంత అడ్మినిస్ట్రేటివ్ స్టాఫ్ తో పాటు స్వతంత్రమైన పరిపాలన సంబంధ నియంత్రణ కూడా దక్కే అవకాశం ఉంది.
| 9
|
NIv2
|
task1013_pib_translation_gujarati_telugu
|
zs_opt
|
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] |
Part 1. Definition
This task is to translate a news commentary given in Italian language into Zhuang language. Translate the input statement into the output language while preserving the numberical values, special characters and proper nouns and context of the commentary done.
Part 2. Example
Cosa è andato storto nel 2008?
Answer: 2008年败在何处？
Explanation: The translation is proper and the important numerical value is preserved.
Part 3. Exercise
Infine, i problemi del Sud Africa riflettono una perdita di fiducia nel governo, una corruzione endemica, enormi esigenze infrastrutturali, e una regolamentazione restrittiva del mercato del lavoro e degli investimenti esteri. E, in termini di riforme, il presidente Jacob Zuma non sembra andare nella giusta direzione.
Answer:
|
最后，南非的问题反映在人们对政府丧失信心、腐败根深蒂固、基础设施需求巨大、劳动力市场和外来投资监管过于严格。而从改革的角度讲，总统祖玛的方向也并不正确。
| 7
|
NIv2
|
task1376_newscomm_translation
|
fs_opt
|
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] |
In this task, you are given two phrases: 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 the Head is capable of the Tail or not. Being capable of something includes general capabilities, such as a human is capable of thinking and reasoning or drinking coffee. It also includes specialized capabilities such as a surgeon is capable of operating on a patient. 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: chicken<sep>Tail: lay eggs
Example solution: Yes
Example explanation: This is a good example. The Head is capable of the Tail.
Problem: Head: shopper<sep>Tail: charge purchases
|
Solution: Yes
| 5
|
NIv2
|
task1215_atomic_classification_capableof
|
fs_opt
|
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] |
Teacher:You will be given three sentences. Read them, then identify a noun phrase (person, place, or thing) or event that is shared between all three sentences. As the output, write the span of the text corresponding to that phrase in each sentence. Keep the order of the sentences, that is, your answer should look like: 1: *a phras from sentence 1e* 2: *a phras from sentence 2* 3: *a phrase from sentence 3*
Teacher: Now, understand the problem? Solve this instance: 1: ( CNN ) Reigning world champion Lewis Hamilton and teammate Nico Rosberg resumed where they left off last season as the 2015 Formula One season kicked off in Melbourne . 2: Rosberg , who won last year 's GP at Albert Park , was fastest around the Melbourne street circuit on Friday , finishing 0.1 second ahead of Hamilton with Sebastian Vettel taking third spot for his new team Ferrari -- the German four-time world champion finished 0.715 seconds off the pace set by his compatriot . 3: Nico Rosberg fastest ahead of team Lewis Hamilton in Australia GP practice .
Student:
|
1: teammate Nico Rosberg 2: Rosberg , who won last year 's GP at Albert Park 3: Nico Rosberg
| 6
|
NIv2
|
task281_points_of_correspondence
|
zs_opt
|
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] |
TASK DEFINITION: Categorize the following sentence into one of the five different emotions: anger, confusion, joy, sadness and neutral.
PROBLEM: I think it’s a bit more complicated than that, it also would appear I may have been misunderstood.
SOLUTION: confusion
PROBLEM: Sadly, he seems immune to bans. He also dodges them with alts like [NAME]
SOLUTION: sadness
PROBLEM: We do what we must because we can
SOLUTION:
|
neutral
| 8
|
NIv2
|
task889_goemotions_classification
|
fs_opt
|
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Given the background description of some cooking related query, summarize the question into a title
[Q]: I always keep bread around, home-made or otherwise. Is there a way to keep it from molding, or at least delay the process?I've tried the fridge with some success (extra day or two), but I don't like my bread that cold to eat.I've tried zip-top bags with no success (seems to mold faster).Bread-box didn't seem to make any difference in time.Thanks
[A]: delaying moldy bread
[Q]: I have a large batch of corn bread that's about to go bad, a situation I'd like to salvage by turning it into corn bread pudding. Unfortunately, all of the recipes I can find online start from base ingredients, or corn muffin mix, rather than using completed corn bread as an ingredient. Recipes for bread pudding don't have this problem; they don't expect you to start from flour :)Can I just substitute corn bread for wheat bread in a bread pudding recipe and get palatable results? I'm not at all sure. If not, what would people suggest I do to my corn bread, to turn it into corn bread pudding?
[A]: Making corn bread pudding from corn bread
[Q]: We're going to try canning some homemade chili with canned kidney beans. Question: Would it be best to add the beans right before canning so they don't get over cooked or do you think there would be little difference if they were cooked with the chili before canning. I'm trying to avoid mushy beans but would like to cook a big pot and can the left overs. I usually add the beans in the last half hour of cooking anyway.
[A]:
|
Canning chili with beans
| 5
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NIv2
|
task1637_doqa2.1_cooking_text_summarization
|
fs_opt
|
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] |
Definition: A piece of text from one of these 5 languages - French, English, Dutch, Somali, Tagalog is given. Generate the language to which the text belongs.
Input: Text: 26 Ilaahna wuxuu yidhi, Aan nin inoo eg ka samayno araggeenna, oo iyagu ha xukumeen kalluunka badda, iyo haadda hawada, iyo xoolaha, iyo dhulka oo dhan, iyo waxa dhulka gurguurta oo dhan.
Output:
|
Somali
| 2
|
NIv2
|
task447_opus_paracrawl_classification
|
zs_opt
|
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] |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Spanish.
Ex Input:
אבל למרבה המזל, תנועת הנגד קיימת גם בקרב ההורים ואפשר למצוא ערים בארה "" ב שמתאחדות אלו עם אלו ואוסרות על קיום חוגים ביום מסוים בחודש, כדי שאנשים יוכלו, להוריד קצת מהלחץ, לבלות עם המשפחה ולהאט.
Ex Output:
Pero por suerte hay una reacción también de los padres, y están descubriendo que las ciudades de los Estados Unidos se estan uniendo y prohibiendo las tareas extracurriculares en un día particular del mes, de manera que la gente pueda aflojarse y tener un poco de tiempo con la familia, y desacelerar.
Ex Input:
מוטורולה מייצרת את הטלפון הנפוץ ביותר, ואתם יכולים לראות שהם בשימוש השרות החשאי, בלחימה, זה תקן מאוד מאוד נפוץ בארה "" ב ובארצות אחרות.
Ex Output:
Motorola fabrica uno de los más utilizados, y Uds. pueden ver que son utilizados por el Servicio Secreto y también en combate, es un estándar bastante, bastante común en EE.UU. y en otros lugares.
Ex Input:
אז שלוש פיסות מידע לגבי כל מדינה... שלוש פיסות מידע.
Ex Output:
|
Tres grupos de variables para cada país, tres datos.
| 1
|
NIv2
|
task1236_ted_translation_he_es
|
fs_opt
|
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] |
Detailed Instructions: Given a statement, generate a question such that the answer is contained in that statement.
Problem:Some animals that eat grass have more than one stomach.
Solution:
|
How many stomachs do some animals that eat grass have?
| 8
|
NIv2
|
task1580_eqasc-perturbed_question_generation
|
zs_opt
|
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0.8238030672073364,
0.6416745781898499,
-0.09724491834640503,
0.7037090063095093,
-0.7808308005332947,
-0.5490757822990417,
-0.24797961115837097
] |
Instructions: Given a sentence in Hindi, generate a new Hindi 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.
Input: यदि आप एक विचार सही करना चाहते हैं तो आपको एक इंजन.
Output:
|
अगर आप किसी विचार को समझाना चाहते हैं तो आपको कल्पना करनी चाहिए ।
| 3
|
NIv2
|
task407_mickey_hi_sentence_perturbation_generation
|
zs_opt
|
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] |
Given the task definition and input, reply with output. In this task you will be given a process, and a question. The process contains a sequence of steps that happen in order. The question asks about the effect of a certain event on another event. If the first event has a positive effect on the second event, answer with "for", if it has a negative effect, answer with "against". If there's no causal relationship between the two, answer with "none".
Process: -Cells obtain glucose and oxygen -The glucose and oxygen create carbon dioxide -The cells release energy -The cells don't have enough oxygen to repeat this -The cells obtain more oxygen from the air -The cells repeat this process.
Question: What is the effect of the cells repeat the process more on less oxygen reaching the body.?
|
against
| 5
|
NIv2
|
task1727_wiqa_what_is_the_effect
|
zs_opt
|
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] |
Detailed Instructions: In this task you will be given a list of strings and you need to concatenate them.
Problem:['i', 'Ahab,', 'C', 'W', 'v', 'ship', 'r']
Solution:
|
iAhab,CWvshipr
| 8
|
NIv2
|
task079_conala_concat_strings
|
zs_opt
|
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] |
You are given an open-domain question from an open movie database. Your task is to provide an answer to that question. Try to only include the answer. Do not put it in a sentence.
Input: Consider Input: Mudhoney, is it any good?
Output: good
Input: Consider Input: the movie Tennessee Johnson, when was it released?
Output: 1942
Input: Consider Input: who starred in Camel Spiders?
|
Output: C. Thomas Howell, Brian Krause, Frankie Cullen, Melissa Brasselle
| 2
|
NIv2
|
task615_moviesqa_answer_generation
|
fs_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.
Read the given query and classify it as a 'Good' or 'Bad' query depending on how well the query is formed, 'Bad' being the expected output for a not so well formed query and 'Good' being the expected output for a well formed query. A query may be wrong based on common sense or general facts, but if it is well formed, you should answer with Good.
What is the scientific name of the tortoise ?
Solution: Good
Why? The output for the query is Good because the query has no grammatical, punctuation or spelling errors.
New input: Symbol of the german nazi partyt ?
Solution:
|
Bad
| 0
|
NIv2
|
task673_google_wellformed_query_classification
|
fs_opt
|
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TASK DEFINITION: Answer the question from the given passage. Your answer should be directly extracted from the passage, and it should be a single entity, name, or number, not a sentence.
PROBLEM: Passage: Child labour is common in Kenya. Most working children are active in agriculture. In 2006, UNICEF estimated that up to 30% of girls in the coastal areas of Malindi, Mombasa, Kilifi, and Diani were subject to prostitution. Most of the prostitutes in Kenya are aged 9–18. The Ministry of Gender and Child Affairs employed 400 child protection officers in 2009. The causes of child labour include poverty, the lack of access to education and weak government institutions. Kenya has ratified Convention No. 81 on labour inspection in industries and Convention No. 129 on labour inspection in agriculture. Question: What percent of girls are in prostution in Kenyas coastal areas?
SOLUTION: up to 30%
PROBLEM: Passage: When considering computational problems, a problem instance is a string over an alphabet. Usually, the alphabet is taken to be the binary alphabet (i.e., the set {0,1}), and thus the strings are bitstrings. As in a real-world computer, mathematical objects other than bitstrings must be suitably encoded. For example, integers can be represented in binary notation, and graphs can be encoded directly via their adjacency matrices, or by encoding their adjacency lists in binary. Question: In the encoding of mathematical objects, what is the way in which integers are commonly expressed?
SOLUTION: binary notation
PROBLEM: Passage: The needs of soy farmers have been used to justify many of the controversial transportation projects that are currently developing in the Amazon. The first two highways successfully opened up the rainforest and led to increased settlement and deforestation. The mean annual deforestation rate from 2000 to 2005 (22,392 km2 or 8,646 sq mi per year) was 18% higher than in the previous five years (19,018 km2 or 7,343 sq mi per year). Although deforestation has declined significantly in the Brazilian Amazon between 2004 and 2014, there has been an increase to the present day. Question: What did creating highways in the Amazon rainforest lead to?
SOLUTION:
|
increased settlement and deforestation
| 8
|
NIv2
|
task1608_xquad_en_answer_generation
|
fs_opt
|
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] |
Q: Given a sentence and two mentions from the text (arguments), indicate a phrase (a verb or noun phrase) that describes the relationship between the provided arguments.
Sentence: 'Patrick Bannon was born in Thurlas , County Tipperary , Ireland , in April , 1814 .', Argument/Subject 1: 'patrick', Argument/Subject 2: 'ireland'
A:
|
be bear in
| 7
|
NIv2
|
task676_ollie_relationship_answer_generation
|
zs_opt
|
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] |
Q: Given a passage classify if the passage has a definite objective/aim/goal or not. Output '1' if the passage has a defininte objective/aim/goal and output '0' if the passage does not have a definite objective/aim/goal.
Recent whole genome association studies have independently identified multiple prostate cancer (PC) risk variants on 8q24. We have evaluated association of common variants in this region with PC susceptibility and tumor aggressiveness in a sample of European American men.', "Forty-nine tagging SNPs including three previously reported significant variants (rs1447295, rs6983267, rs16901979) and seven variants in the 5' upstream region of the MYC proto-oncogene were tested for association with susceptibility to PC and tumor aggressiveness in 596 histologically verified PC cases and 567 ethnically matched controls.", 'Significant associations with susceptibility to PC were found at 17 SNPs, four of which (rs1016342, rs1378897, rs871135, and rs6470517) remained significant after adjusting for multiple corrections. One of the associated SNPs, rs871135, is located in the putative gene POU5F1P1 within the 8q24 region. An in slico analysis showed that the associated variant of this SNP alters a transcription factor implicating a plausible regulatory role. Additionally, one of the significantly associated SNPs, rs6470517, with PC susceptibility showed a significant over-representation of the G allele in cases with aggressive tumor.
A:
|
0
| 7
|
NIv2
|
task848_pubmedqa_classification
|
zs_opt
|
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] |
Given a sentence, generate a most likely context or previous statement. The previous statement should be relevant to the given statement.
Q: The troll then walks up to someone, who has fallen on the ground.
A: Unfazed by the bullets, he crushes the last deputy's head.
****
Q: She's shown again tying her shoes close up and a woman helps her off the bed.
A: The girl then puts shoes on her feet and ties the laces.
****
Q: The family of skiers makes it to the bottom of the slope and congratulate each other.
A:
|
The skiers cut back and fourth down a steep ski slope hill.
****
| 4
|
NIv2
|
task455_swag_context_generation
|
fs_opt
|
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] |
instruction:
In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".
question:
Paragraph: The present study was undertaken to evaluate chikungunya virus (CHIKV) proteins for RNAi suppressor activity. We systematically analyzed all nine CHIKV proteins for RNAi suppressor activity using Sf21 RNAi sensor cell line based assay. Two non-structural proteins, namely, nsP2 and nsP3 were found to exhibit RNAi suppressor activity. We further validated the findings in natural hosts, namely in Aedes and in mammalian cell lines and further through EMSA and Agrobacterium infiltration in GFP silenced transgenic tobacco plants. Domains responsible for maximum RNAi suppressor activity were also identified within these proteins. RNA binding motifs in these domains were identified and their participation in RNAi suppression evaluated using site directed mutagenesis. Sequence alignment of these motifs across all species of known alphaviruses revealed conservation of these motifs emphasizing on a similar role of action in other species of alphaviruses as well. Further validation of RNAi suppressor activity of these proteins awaits establishment of specific virus infection models. RNA interference (RNAi) is a conserved evolutionary mechanism designed to impart an antiviral defence system across organisms ranging from plants, fungi, arthropods and nematodes 1-4 . The phenomenon, triggered by the production of double stranded RNA (dsRNA) by the pathogen upon infection, leads to the activation of the RNA interference silencing complex (RISC) by loading of dsRNA/siRNA into the complex ultimately leading to cleavage of the viral RNA 5,6,7 . Several components of RISC participate in the cleavage, most important being ribonuclease III Dicer (DCR) and Argonaute protein (AGO). Dicer acts on dsRNA to generate small RNA (sRNA) that are loaded into the AGO, resulting in cleavage 8,9 ; however, some RNAi pathways are independent of Dicer and other components like RNA-dependent RNA polymerase (RdRP) produce short RNA transcripts that directly bind to AGO 10 . Similarly, much is now known about the Piwi pathway that is specifically active in the germline 11 . In response to RNAi in plants and insects, viruses infecting these systems utilise some of their own proteins/sequence elements that counteract the antiviral RNAi pathway 12 . These viral suppressors of RNAi (VSRs) act through different mechanisms, either by binding to long dsRNA and protecting them from Dicer 7,13 or short RNAs 14 or through multi-mode mechanisms 15,16 . Recently it has been shown that some viruses encode host-specific VSRs due to co-evolution of the virus and the host, emphasising on the importance of analysing suppressor activity in relevant host 17 . Amongst medically important pathogenic viruses, arboviruses form an important subset of viruses due to the complexity of their host preferences 18 . These viruses, mainly constituted by genera flavivirus and alphavirus,
Title: Analysis of chikungunya virus proteins reveals that non-structural proteins nsP2 and nsP3 exhibit RNA interference (RNAi) suppressor activity OPEN
answer:
False
question:
Paragraph: Delineation of the intricacies of protein function from macromolecular structure constitutes a continual obstacle in the study of cell and pathogen biology. Structure-based phylogenetic analysis has emerged as a powerful tool for addressing this challenge, allowing the detection and quantification of conserved architectural properties between proteins, including those with low or no detectable sequence homology. With a focus on viral protein structure, we highlight how a number of investigations have utilized this powerful method to infer common functionality and ancestry.
Title: Unraveling virus relationships by structure-based phylogenetic classification
answer:
True
question:
Paragraph: Foot-and-mouth disease virus (FMDV) is the type species of the Aphthovirus genus within the Picornaviridae family. Infection of cells with positive-strand RNA viruses results in a rearrangement of intracellular membranes into viral replication complexes. The origin of these membranes remains unknown; however induction of the cellular process of autophagy is beneficial for the replication of poliovirus, suggesting that it might be advantageous for other picornaviruses. By using confocal microscopy we showed in FMDV-infected cells co-localization of non-structural viral proteins 2B, 2C and 3A with LC3 (an autophagosome marker) and viral structural protein VP1 with Atg5 (autophagy-related protein), and LC3 with LAMP-1. Importantly, treatment of FMDV-infected cell with autophagy inducer rapamycin, increased viral yield, and inhibition of autophagosomal pathway by 3-methyladenine or small-interfering RNAs, decreased viral replication. Altogether, these studies strongly suggest that autophagy may play an important role during the replication of FMDV. Published by Elsevier Inc. Virology 410 (2011) 142-150
Title: Foot-and-mouth disease virus utilizes an autophagic pathway during viral replication
answer:
|
True
| 9
|
NIv2
|
task1162_coda19_title_classification
|
fs_opt
|
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0.2889117896556854
] |
Definition: In this task, you are given two sentences in the English language and your task is to classify them into one of their discourse types. A discourse type is an indicator to classify the given two sentences on the basis of a co-text as well as a relevant context. There are 13 discourse types in total which are 'SINGLE_S_COORD', 'SINGLE_CATAPHORA', 'SINGLE_CONN_INNER', 'SINGLE_APPOSITION', 'SINGLE_VP_COORD', 'SINGLE_CONN_START', 'PAIR_ANAPHORA', 'PAIR_CONN', 'SINGLE_RELATIVE', 'SINGLE_CONN_INNER_ANAPHORA', 'SINGLE_S_COORD_ANAPHORA', 'PAIR_CONN_ANAPHORA' and 'PAIR_NONE'.
Input: Sentence 1:Haru acts as a decoy to distract the Onis in order to let his friends enter their ship , Syaoran . Sentence 2:However , upon their arrival they are trapped in a prison and Plue and Griffon take advantage of their height to search for a way out .
Output:
|
PAIR_CONN_ANAPHORA
| 2
|
NIv2
|
task564_discofuse_classification
|
zs_opt
|
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] |
Given the task definition and input, reply with output. In this task you are given a premise and two alternatives in Italian. You must choose the alternative that is more plausibly the cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
La frutta matura rimase esposta al sole.
(1)È stata mangiata.(2)Si è avvizzita.
|
2
| 5
|
NIv2
|
task1172_xcopa_commonsense_reasoning_it
|
zs_opt
|
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Q: In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.
Deep learning methods have achieved high performance in sound recognition tasks. Deciding how to feed the training data is important for further performance improvement. We propose a novel learning method for deep sound recognition: Between-Class learning (BC learning). Our strategy is to learn a discriminative feature space by recognizing the between-class sounds as between-class sounds. We generate between-class sounds by mixing two sounds belonging to different classes with a random ratio. We then input the mixed sound to the model and train the model to output the mixing ratio. The advantages of BC learning are not limited only to the increase in variation of the training data; BC learning leads to an enlargement of Fisher’s criterion in the feature space and a regularization of the positional relationship among the feature distributions of the classes. The experimental results show that BC learning improves the performance on various sound recognition networks, datasets, and data augmentation schemes, in which BC learning proves to be always beneficial. Furthermore, we construct a new deep sound recognition network (EnvNet-v2) and train it with BC learning. As a result, we achieved a performance surpasses the human level.
A:
|
We propose an novel learning method for deep sound recognition named BC learning.
| 7
|
NIv2
|
task668_extreme_abstract_summarization
|
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 are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to classify the command into one of these seven categories: (1) majority, (2) unique, (3) superlative, (4) count, (5) comparative, (6) aggregation, and (7) ordinal.
Here are the defications of each category:
1. majority: Describing the majority values (most or all) over one column, with the scope of all table rows or a subset of rows
2. unique: Describing one unique row, regarding one column, with the scope of all table rows or a subset of rows
3. Superlative: Describing the maximum or minimum value in a column, with the scope of all table rows or a subset of rows
4. Ordinal: Describing the n-th maximum or minimum value in a column, with the scope of all table rows or a subset of rows
5. Comparative: Comparing two rows in the table, regarding their values in one column
6. Count: counting some rows in the table based on the values in one column, with the scope of all table rows or a subset of rows
7. Aggregation: Describing the sum or average value over a column, with the scope of all table rows or a subset of rows.
Here are the definitions of logical operators for understanding of command:
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 the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
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 the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
and { only { filter_eq { all_rows ; margin of victory ; 4 strokes } } ; eq { hop { filter_eq { all_rows ; margin of victory ; 4 strokes } ; tournament } ; barclays scottish open } }
Output:
|
unique
| 1
|
NIv2
|
task212_logic2text_classification
|
zs_opt
|
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] |
In this task, you will be shown a short story with a beginning, two potential middles, and an ending. Your job is to choose the middle statement that makes the story incoherent / implausible by indicating 1 or 2 in the output. If both sentences are plausible, pick the one that makes less sense.
Beginning: Joe had quit his job to travel the world. Middle 1: Joe soon ran out of money and was stranded in America. Middle 2: Joe soon ran out of money and was stranded. Ending: Alas, things didn't work out and he had to return to America.
1
Beginning: I got home from work early. Middle 1: I was very rude to my daughter when I saw her. Middle 2: My daughter was very rude when she saw me. Ending: However, she finally changed her behavior.
1
Beginning: A little boy was in the third grade. Middle 1: He decided this year he would study the minimum. Middle 2: He decided this year he would study hard. Ending: At the end of the year, he did well on his reading test.
|
1
| 0
|
NIv2
|
task070_abductivenli_incorrect_classification
|
fs_opt
|
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] |
Teacher:In this task you are given a premise and two alternatives in Haitian. You must choose the alternative that is more plausibly the cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
Teacher: Now, understand the problem? Solve this instance: Mwen te ajoute sik nan kafe a.
(1)Kafe a te santi fò.(2)Kafe a te gen gou sikre.
Student:
|
2
| 6
|
NIv2
|
task1168_xcopa_commonsense_reasoning_ht
|
zs_opt
|
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] |
This task is about translating a given English language sentence to French.
Q: I've gotta talk to you.
A: - Je dois te parler.
****
Q: Changing by the minute and the record on repeat Took a sip, then another sip, then somebody said to me:
A: Celui d'être déchiré Remplissant mon verre je vois la foule bouger Changeant avec les minutes et ces mêmes musiques qui se répètent
****
Q: Jack: I'll have a mouthful. man:
A:
|
Juste une gorgée.
****
| 4
|
NIv2
|
task1689_qed_amara_translation
|
fs_opt
|
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] |
Instructions: In this task, you are given concept set (with 3 to 5 concepts) that contain mentions of names of people, places, activities, or things. These concept sets reflect reasonable concept co-occurrences in everyday situations. All concepts given as input are separated by "#". Your job is to generate a sentence describing a day-to-day scene using all concepts from a given concept set.
Input: environment#interact#organism
Output:
|
how do organisms in the environment interact with mercury .
| 3
|
NIv2
|
task102_commongen_sentence_generation
|
zs_opt
|
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] |
In this task, you are given two phrases: 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 the Head is capable of the Tail or not. Being capable of something includes general capabilities, such as a human is capable of thinking and reasoning or drinking coffee. It also includes specialized capabilities such as a surgeon is capable of operating on a patient. 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.
[Q]: Head: cat<sep>Tail: chase mice
[A]: Yes
[Q]: Head: PersonX achieves PersonX's aim<sep>Tail: successful
[A]: No
[Q]: Head: barbarian<sep>Tail: battle knight
[A]:
|
Yes
| 5
|
NIv2
|
task1215_atomic_classification_capableof
|
fs_opt
|
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] |
The input is a sentence. The sentence includes an emotion. The goal of the task is to classify the emotion in the sentence to one of the classes: 'fear', 'joy', 'anger', 'sadness'. The emotion mainly depends on the adverb within the sentence.
Adam found himself in a horrible situation.
fear
The situation makes Roger feel ecstatic.
joy
Adam found himself in a threatening situation.
|
fear
| 0
|
NIv2
|
task1338_peixian_equity_evaluation_corpus_sentiment_classifier
|
fs_opt
|
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] |
Given the task definition, example input & output, solve the new input case.
You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Example: How many miles is 43560 ?
What is the national currency of Albania ?
What is the status of the draft today in US ?
Where is the oil plug in a 2004 Harley ?
Output: How many miles is 43560 ?
The output is from the list of given queries and it is not well structured and has grammatical errors when compared to other queries
New input case for you: Are bananas good for your skin ?
Are Patrick Swayze and Kurt Russell brothers ?
How many eggs do green iguanas lay ?
How does the acid rain solution effect on the enviroment ?
Output:
|
How does the acid rain solution effect on the enviroment ?
| 1
|
NIv2
|
task674_google_wellformed_query_sentence_generation
|
fs_opt
|
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] |
Q: In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].
This paper considers the problem of model-based policy search. The authors consider the use of Bayesian Neural Networks to learn a model of the environment and advocate for the $\alpha$-divergence minimization rather than the more usual variational Bayes. The ability of alpha-divergence to capture bi-modality however comes at a price and most of the paper is devoted to finding tractable approximations. The authors therefore use the approach of Hernandez-Lobato et al. (2016) as proxy to the alpha-divergence . The environment/system dynamics is clearly defined as a well as the policy parametrization (section 3) and would constitute a useful reference point for other researchers. Simulated roll-outs, using the learned model, then provide samples of the expected return. Since a model of the environment is available, stochastic gradient descent can be performed in the usual way, without policy gradient estimators, via automatic differentiation tools. The experiments demonstrate that alpha-divergence is capable of capturing multi-model structure which competing methods (variational Bayes and GP) would otherwise struggle with. The proposed approach also compares favorably in a real-world batch setting. The paper is well-written, technically rich and combines many recent tools into a coherent algorithm. However, the repeated use of approximations to original quantities seems to somehow defeat the benefits of the original problem formulation. The scalability and computational effectiveness of this approach is also questionable and I am uncertain if many problem would warrant such complexity in their solution. As with other Bayesian methods, the proposed approach would probably shine in low-samples regime and in this case might be preferable to other methods in the same class (VB, GP).
A:
|
en
| 7
|
NIv2
|
task265_paper_reviews_language_identification
|
zs_opt
|
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] |
You are given a sentence in Polish. Your job is to translate the Polish sentence into Galician.
Ex Input:
To jeden z przykładów.
Ex Output:
É unha desas cousas.
Ex Input:
No i oczywiście im bardziej rozwinięty kraj, tym większe góry śmieci.
Ex Output:
E, obviamente, canto máis desenvolvido sexa o país, maiores serán estas montañas.
Ex Input:
Laboratoria potrafią mierzyć poziom koncentracji.
Ex Output:
|
Pois no laboratorio podemos medir a atención.
| 1
|
NIv2
|
task1261_ted_translation_pl_gl
|
fs_opt
|
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1.0257242918014526,
1.0834847688674927,
0.037748221307992935,
0.5349750518798828,
0.19376951456069946,
-0.699988603591919,
-0.75465989112854,
0.39571383595466614
] |
Detailed Instructions: In this task, you will be shown a short story with a beginning, two potential middles, and an ending. Your job is to choose the middle statement that makes the story coherent / plausible by writing "1" or "2" in the output. If both sentences are plausible, pick the one that makes most sense.
Q: Beginning: Mark had a 9am flight to Chicago. Middle 1: Mark made it to the airport with plenty of time. Middle 2: Mark made it to the airport with no time left. Ending: Mark got lucky and felt relief because he had time to make his flight!
A:
|
1
| 9
|
NIv2
|
task069_abductivenli_classification
|
zs_opt
|
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] |
Generate a correct and concise answer for the question based on the words in the context.
Context : Henk Zanoli (21 April 1923) is a retired lawyer and former member of the Dutch resistance during World War II, who was awarded the honorific title Righteous Among the Nations, but returned his medal after an Israeli air strike killed six of his family members.
Question : Which award was bestowed upon Henk Zanoli?
|
Righteous Among the Nations
| 0
|
NIv2
|
task1327_qa_zre_answer_generation_from_question
|
zs_opt
|
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] |
Q: Given a sentence in the Indonesian(Bahasa variant), provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Dr. Luanne Metz, direktur Klinik MS Calgary di Departemen Klinis Neurosciences, Universitas Calgary dan Kawasan Kesehatan Calgary, menambahkan, "Penemuan ini berpotensi pengobatan MS selangkah lebih jauh dari perawatan masa kini yang menstabilkan penyakit tersebut di tahap awal."
A:
|
カルガリー大学カルガリー・ヘルス・リージョン臨床神経科学学科、カルガリー多発性硬化症クリニック長のルアン・メス博士は「この発見は初期段階で疾病を安定させる現在の治療よりも一歩進んだ多発性硬化症治療の可能性を持っている」
| 7
|
NIv2
|
task1116_alt_id_ja_translation
|
zs_opt
|
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] |
Q: You will be given a trivia clue, and the category it belongs to. You should answer with the best answer that belongs in the category and is described by the clue. For simplicity, answers should be in all lower cased letters.
Category: WHAT ARE YOU... CHICKEN?
Clue: Diced chicken in a rich cream with mushrooms, pimientos, green peppers & sherry is chicken a la this
A:
|
king
| 7
|
NIv2
|
task308_jeopardy_answer_generation_all
|
zs_opt
|
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] |
Teacher:You are given a sentence in Galician. Your job is to translate the Galician sentence into Hebrew.
Teacher: Now, understand the problem? Solve this instance: Así que me pediron que me achegase a ver a Rosalie, a señora maior.
Student:
|
הם ביקשו שאגיע ואפגוש את רוזלי, הגברת המבוגרת.
| 6
|
NIv2
|
task1242_ted_translation_gl_he
|
zs_opt
|
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