inputs stringlengths 38 313k | targets stringlengths 0 4.86k | _template_idx int64 0 9 | _task_source stringclasses 1
value | _task_name stringlengths 19 85 | _template_type stringclasses 2
values | embedding listlengths 1.02k 1.02k |
|---|---|---|---|---|---|---|
Teacher: In this task, you are given an input list A. You need to convert all the alphabets in the list with a number representing their position in the English alphabet. E.g., replace A by 1, B by 2, a by 1, b by 2, and so on.
Teacher: Now, understand the problem? If you are still confused, see the following example:
... | 1, 10, 13, 5159, 8971, 4351, 5869, 8061 | 2 | NIv2 | task622_replace_alphabets_in_a_list_by_their_position_in_english_alphabet | fs_opt | [
-0.2833157181739807,
-0.006760191638022661,
0.3212268352508545,
-0.686622142791748,
0.034357212483882904,
-0.7422475814819336,
-0.27073004841804504,
0.5960067510604858,
-0.17992787063121796,
0.11034000664949417,
-0.13550278544425964,
-0.28469347953796387,
0.10084431618452072,
-0.7721879482... |
Teacher:Generate an appropriate single-sentence summary for the given text such that it includes the main topic of the text.
Teacher: Now, understand the problem? Solve this instance: More than 5,000 people were stuck at or near the border and at one point several tried to storm the fence. Four thousand more arrived by... | Thousands of migrants and refugees have been stranded near Athens and on Greece's northern border after Macedonia stopped allowing Afghans in. | 6 | NIv2 | task1357_xlsum_summary_generation | zs_opt | [
0.5553761720657349,
0.060182370245456696,
-0.3950580656528473,
-0.4501004219055176,
0.539367139339447,
0.1224772110581398,
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0.9184368252754211,
-0.17093154788017273,
0.8859012126922607,
0.14437556266784668,
0.5085163116455078,
-0.7057024240493774,
0.36427438259124756,
... |
Detailed Instructions: In this task, you will be given two sentences sentence1 and sentence2. You should decide whether the second sentence is entailed(agreed) by the first sentence. If it does entail, answer "yes", else answer "no".
Q: sentence1:organization_founder is emulating organization_founder sentence1:organiz... | yes | 9 | NIv2 | task970_sherliic_causal_relationship | zs_opt | [
-0.2819143533706665,
0.5562681555747986,
0.35929563641548157,
-0.26532578468322754,
-0.17143359780311584,
-1.0449782609939575,
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-0.18710577487945557,
-0.6519776582717896,
-1.1722158193588257,
-0.7208926677703857,
-0.13316500186920... |
Detailed Instructions: In this task, you're shown a three-part story, with a beginning, middle, and ending. Your job is to slightly modify the middle part, so that the whole story becomes unlikely, improbable, or inconsistent. Generated sentences must minimally alter the given middle, with at most 4 new words added/exi... | I changed genders but everyone knew me. | 8 | NIv2 | task068_abductivenli_incorrect_answer_generation | zs_opt | [
0.6300203800201416,
0.5184572339057922,
-0.3237842917442322,
-0.009620679542422295,
-0.35361582040786743,
0.2419891357421875,
0.37311726808547974,
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-0.29081109166145325,
-0.592448353767395,
0.24812422692775726,
-0.1264842003583908,
-0.344598621129989... |
Given reviews from Amazon, classify those review based on their content into two classes: Negative or Positive.
Example input: I've read this book with much expectation, it was very boring all through out the book
Example output: Negative
Example explanation: Review writer does not like the book because it was boring,... | Positive | 3 | NIv2 | task493_review_polarity_classification | fs_opt | [
-0.41648828983306885,
-0.1232265904545784,
0.2899414002895355,
-0.8562746047973633,
0.5021851062774658,
-0.6505331993103027,
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0.2322237342596054,
-0.47717297077178955,
-0.9521596431732178,
-0.4804384112358093,
... |
Instructions: In this task, you are given a news article. Your task is to classify the article to one out of the four topics 'World', 'Sports', 'Business', 'Sci/Tech' if the article's main topic is relevant to the world, sports, business, and science/technology, correspondingly. If you are not sure about the topic, cho... | Sci/Tech | 3 | NIv2 | task379_agnews_topic_classification | zs_opt | [
-0.9374957084655762,
0.005570707842707634,
-0.09829767048358917,
0.5962483286857605,
0.312009334564209,
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-0.3984651565551758,
-0.11878814548254013,
-0.3135809302330017,
0.08311919122934341,
-0.2959038019180298,
-0.116065613925457,
-0.35528114438056946,
-0.337140560150146... |
Detailed Instructions: In this task, you are given a sentence in the Bulgarian language and corresponding English translation of this sentence. Here, your job is to generate label "yes" if translation is right, otherwise generate label "no".
See one example below:
Problem: Bulgarian: Състав на Парламента: вж. протоколи... | no | 4 | NIv2 | task273_europarl_classification | fs_opt | [
-0.7505723237991333,
0.34508273005485535,
0.12622517347335815,
0.4689132273197174,
0.1697198450565338,
-0.9245712757110596,
0.7838999032974243,
0.8709333539009094,
0.10512852668762207,
0.616456925868988,
-0.42418497800827026,
0.7397226691246033,
-0.3299950361251831,
0.08836757391691208,
... |
Detailed Instructions: In this task, you're given a question, along with a context passage which has extra information available on certain terms mentioned in it, i.e., the proper nouns in the passage. Your job is to determine whether information from more than one term is needed to answer the question. Indicate your c... | b | 8 | NIv2 | task232_iirc_link_number_classification | zs_opt | [
0.2584502100944519,
0.6446620225906372,
-0.44552475214004517,
0.007895243354141712,
0.40116047859191895,
-0.21787330508232117,
0.6803029775619507,
0.8801747560501099,
-0.13323476910591125,
0.5063368082046509,
0.14815162122249603,
0.2705945372581482,
-0.17792311310768127,
0.4189971685409546... |
Given a scientific question, generate an incorrect answer to the given question. The incorrect answer should be a plausible alternative to the correct answer. The answer should be some other item belonging to the same category as the correct answer but should be incorrect.
One example is below.
Q: What are arteries, ve... | blue giant | 9 | NIv2 | task592_sciq_incorrect_answer_generation | fs_opt | [
0.856131374835968,
1.0664085149765015,
-0.5210819840431213,
0.6134762763977051,
-0.41725021600723267,
-0.620934784412384,
0.23345965147018433,
0.33816853165626526,
0.06992708146572113,
-0.35696569085121155,
0.4990731477737427,
-0.47710463404655457,
-0.4916177988052368,
-0.02326967567205429... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given a command in a limited form of natural language, provide the correct sequence of actions that executes the command to thus navigate an agent in its environment. A command can be broken down int... | I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT I_TURN_LEFT | 0 | NIv2 | task128_scan_structured_text_generation_command_action_short | fs_opt | [
0.22003448009490967,
0.6777924299240112,
-0.23418743908405304,
-0.09724894165992737,
0.26904159784317017,
0.302818238735199,
0.5930042266845703,
0.17270898818969727,
-0.3120979964733124,
-0.4936026334762573,
-0.628505527973175,
-0.5769752264022827,
-0.5446373820304871,
-0.02514925040304660... |
Q: The input is a tweet which can be classified as Hate Speech, Offensive or Normal. Given such a tweet, output the class the tweet belongs to. Hate Speech will contain threatening language towards the community targeted. Offensive language will contain abusive or discriminatory language towards the community targeted.... | Offensive | 7 | NIv2 | task1502_hatexplain_classification | zs_opt | [
-0.6708898544311523,
0.8379555940628052,
0.41690438985824585,
0.5452263951301575,
-0.1865137815475464,
-1.3596893548965454,
-0.06827220320701599,
0.8196955323219299,
0.8199427127838135,
0.20323413610458374,
-0.5117160081863403,
-0.054680995643138885,
-0.6527248024940491,
-0.818427443504333... |
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 triplets. Each triplet is in the form of [subject, predicate, object]. Your task is to generate proper sentence that utilizes these triples. The objective is to construct ... | From 1989-Present, the previous Ship was RNN HNLMS Evertsen (F815). | 0 | NIv2 | task1409_dart_text_generation | fs_opt | [
-0.3436030447483063,
0.43040937185287476,
-0.5068866014480591,
-0.630603551864624,
-0.16416481137275696,
-0.11646615713834763,
0.8939940333366394,
0.526879072189331,
-0.31482794880867004,
-0.1758059859275818,
-0.6902648210525513,
0.21842660009860992,
-0.36436206102371216,
-0.08620172739028... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Sentence 1: I've been needing a divorce for a year, she added. Sentence 2: She went ahead and s... | 1 | 0 | NIv2 | task198_mnli_domain_classification | zs_opt | [
-0.4861668348312378,
0.47995680570602417,
0.5194255113601685,
0.2075524628162384,
0.15719369053840637,
0.1327080875635147,
0.051907628774642944,
0.7958480715751648,
0.030136151239275932,
-0.2732657790184021,
-0.8015226125717163,
-0.49172165989875793,
-0.8451221585273743,
-0.502332210540771... |
Given the task definition and input, reply with output. In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Review: MI... | yes | 5 | NIv2 | task285_imdb_answer_generation | zs_opt | [
-0.3513087034225464,
0.1443874090909958,
-0.06956788897514343,
0.5120872855186462,
0.10424940288066864,
-0.10540394484996796,
0.10294228047132492,
0.8352370262145996,
-0.40606600046157837,
-0.15379060804843903,
-0.24273383617401123,
-0.6181259155273438,
0.07295213639736176,
-0.676357030868... |
You are given an original reference as well as a system reference. Your task is to judge the quality of the system reference. If the utterance is grammatically correct and fluent output 1, else output 0.
System Reference: so you are looking for something in the inexpensive price range, is that correct?
Original Refere... | 1
| 0 | NIv2 | task1283_hrngo_quality_classification | fs_opt | [
-0.8075926303863525,
1.0076160430908203,
-0.28638872504234314,
0.37773311138153076,
0.07833360880613327,
-1.077498435974121,
1.215381145477295,
0.6098308563232422,
-0.08219647407531738,
-0.024803508073091507,
-0.6615997552871704,
0.07154862582683563,
-0.4610394835472107,
-0.236129164695739... |
Q: In this task, you will be presented with a question, a word, and a POS tag. You have to determine whether the part-of-speech tag of the given word in the question is equal to the given POS tag or not. Give your answer with True or False. Here is the Alphabetical list of part-of-speech tags used in this task: CC: Coo... | False | 7 | NIv2 | task346_hybridqa_classification | zs_opt | [
0.04624268040060997,
-0.180148184299469,
-0.26857975125312805,
0.43880578875541687,
-0.05814364552497864,
-0.818375825881958,
0.6853809356689453,
0.5161524415016174,
-0.18568390607833862,
0.26536130905151367,
-0.45011088252067566,
0.07940276712179184,
-0.06771480292081833,
0.19955189526081... |
Teacher: Write a correct answer to the given question based on its associated fact. Make sure that your answer is contained in the associated fact. Don't be creative and introduce any new word that is not mentioned in the associated fact! Remember that the associated fact has been rearranged to form the question. So, t... | on cancer cells. | 2 | NIv2 | task041_qasc_answer_generation | fs_opt | [
-0.22590774297714233,
0.3665105402469635,
-0.032827891409397125,
-0.21633905172348022,
-0.5229378938674927,
-1.0649213790893555,
-0.039804812520742416,
0.7354743480682373,
-0.23381248116493225,
-0.2462989091873169,
-1.3277976512908936,
0.3996243476867676,
-0.5742594003677368,
-0.3248518705... |
Instructions: In this task, you are given a sentence which is either in the Gujarati language or English language. You task is to identify the language of input sentence. Input sentence can be in Gujarari or English language only and also it cannot have two languages at a time.
Input: Bicycle rider in black and orange ... | English | 3 | NIv2 | task441_eng_guj_parallel_corpus_gu-en_language_identification | zs_opt | [
-0.13475286960601807,
0.17475347220897675,
0.24022993445396423,
-0.12068258225917816,
0.28106871247291565,
-0.5804744958877563,
0.006568545009940863,
-0.07034237682819366,
0.4701191782951355,
-0.28858083486557007,
-0.5783337950706482,
0.08928925544023514,
-0.05574475973844528,
-0.221579059... |
Detailed Instructions: You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Polish.
Q: Ella no era infeliz en absoluto.
A: | W ogóle nie była przygnębiona. | 9 | NIv2 | task1102_ted_translation_es_pl | zs_opt | [
-0.31485259532928467,
1.515712857246399,
-0.08331777900457382,
-0.19234910607337952,
-0.2325717955827713,
-0.7219956517219543,
0.8543329238891602,
-0.15120074152946472,
-0.16453292965888977,
-0.38819757103919983,
0.30524197220802307,
0.22669333219528198,
-0.39336010813713074,
-0.0041476604... |
Given the task definition and input, reply with output. In this task, you need to reverse the order of words in the given sentence.
Sentence: stop sign in front of white government building with cupola
| cupola with building government white of front in sign stop | 5 | NIv2 | task376_reverse_order_of_words | zs_opt | [
-0.6601990461349487,
0.6280230283737183,
0.5272705554962158,
-0.2976033687591553,
-0.44326967000961304,
0.22521349787712097,
-0.34020328521728516,
0.8820759057998657,
0.6066449284553528,
0.30943647027015686,
-0.3846929371356964,
-0.06362377852201462,
0.39360901713371277,
-0.517465889453887... |
In this task, you need to count the number of words in a sentence that contain the given letter
[Q]: Sentence: 'a grey cat sitting in a metal kitchen sink next to cans of soda'. How many words contain the letter 't' in the sentence.
[A]: 6
[Q]: Sentence: 'an older fighter plan sitting next to a group military men'. ... | 3
| 5 | NIv2 | task161_count_words_containing_letter | fs_opt | [
-0.8044677376747131,
1.0651037693023682,
-0.8127021789550781,
-0.7441601753234863,
0.378970742225647,
-0.39992403984069824,
-0.22981184720993042,
-0.016563180834054947,
0.19935613870620728,
-0.21582168340682983,
0.35034361481666565,
0.31887537240982056,
-0.391603946685791,
0.02702328562736... |
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".
One example: Paragraph: The severe acute respiratory sy... | False | 6 | NIv2 | task1162_coda19_title_classification | fs_opt | [
0.5751769542694092,
0.4245274066925049,
-0.417475163936615,
0.03723341226577759,
0.644513726234436,
-0.10410316288471222,
0.7318779230117798,
1.2017760276794434,
-0.30964499711990356,
1.0059778690338135,
-0.2477293163537979,
1.0437936782836914,
-0.11000767350196838,
0.19058263301849365,
... |
Detailed Instructions: Given a sentence in English language, translate the sentence to Igbo language keeping the meaning of the original sentence intact
See one example below:
Problem: English sentence: How is this possible
Solution: Olee kwere omume?
Explanation: The Igbo translation means the same as the original sen... | Ọ pụrụ ịbụ n'ihi na ị, n'onwe, ma ọ bụ azụmahịa, ma ọ bụ ọnọdụ dị ka a ebe ihe na a na-aga nwere kwụsị wee laghachi mmalite ma malite ọzọ. | 4 | NIv2 | task452_opus_paracrawl_en_ig_translation | fs_opt | [
0.019702104851603508,
0.6717662215232849,
0.4155026376247406,
-0.2505035400390625,
0.24146214127540588,
-1.289056658744812,
0.6026198267936707,
0.7630363702774048,
-0.04382721334695816,
-0.38695913553237915,
-0.33838602900505066,
0.08212442696094513,
-0.7758926153182983,
-0.086258433759212... |
Given the task definition and input, reply with output. In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, b... | Clinton | 5 | NIv2 | task303_record_incorrect_answer_generation | zs_opt | [
-0.43120014667510986,
0.8560441732406616,
0.44520655274391174,
0.24642392992973328,
0.11752580106258392,
0.18037836253643036,
-0.3748261332511902,
1.1222639083862305,
-0.4223018288612366,
0.7580317258834839,
-0.1600562483072281,
0.5518420934677124,
-0.10884217172861099,
-0.0765602886676788... |
Given a category and a set of five words, find the word from the set that does not belong (i.e. is the least relevant) with the other words in the category. Words are separated by commas.
Let me give you an example: Category: construction
Words: excavator, crane, pelican, hoist, upraise
The answer to this example can... | touching | 8 | NIv2 | task141_odd-man-out_classification_category | fs_opt | [
-0.013145201839506626,
0.7049937844276428,
-0.0807253047823906,
0.08107073605060577,
0.19956304132938385,
0.23317211866378784,
0.17450371384620667,
0.37479549646377563,
0.04891738295555115,
-0.2692887485027313,
-1.0272141695022583,
0.1505875587463379,
-0.6164498329162598,
0.078531756997108... |
You are given a sentence in Spanish. Your job is to translate the Spanish sentence into English.
Ex Input:
Eso sería un error.
Ex Output:
That would be a mistake.
Ex Input:
Por eso cuando un terrorista escribe a alguien que no conocemos pero realiza o apoya actividades terroristas, o alguien que viola sanciones int... | You could find the nodes, though, and then you went, and you go, "" Right, I've got to investigate these people.
| 1 | NIv2 | task1226_ted_translation_es_en | fs_opt | [
-0.7272558212280273,
0.07251708209514618,
0.04067573696374893,
0.3656505346298218,
0.0014312670100480318,
-0.5558247566223145,
-0.007959895767271519,
1.5036956071853638,
0.1980774998664856,
0.37734752893447876,
-0.582390308380127,
0.13973847031593323,
-0.8236907720565796,
-0.67941880226135... |
In this task, you will be presented with a question having multiple possible answers in German language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Q: Question: Manche Prominente finden es nützlich, an die Öffentlichkeit zu gehen, nachdem sie bei... | C | 4 | NIv2 | task1138_xcsr_de_commonsense_mc_classification | zs_opt | [
-0.05958858132362366,
0.3010830283164978,
-0.24778291583061218,
0.5564254522323608,
0.09995099902153015,
0.06485183537006378,
0.5235699415206909,
0.7591179609298706,
0.3424866497516632,
-0.3892887830734253,
-0.3536618649959564,
0.5424000024795532,
-0.4464556574821472,
-0.470682293176651,
... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Sentence 2 contradicts sentence 1. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to c... | A dog leaps to catch the ball that the boy threw to him. | 8 | NIv2 | task185_snli_contradiction_to_neutral_text_modification | fs_opt | [
-0.29713964462280273,
0.5965664386749268,
0.48731729388237,
-0.5136082172393799,
0.31948357820510864,
-0.4104226231575012,
-0.5337831974029541,
1.206478238105774,
0.009359493851661682,
-0.1419425904750824,
-0.80103600025177,
-0.16444894671440125,
-0.9515551328659058,
-0.5253973007202148,
... |
Definition: Given a simple high-school level math question, you are required to solve it and provide the final answer. The final answer is always a single number. These questions can range from a variety of topics like simple arithmetic, solving equations, converting a quantity from one unit to another, finding remaind... | 18 | 2 | NIv2 | task835_mathdataset_answer_generation | zs_opt | [
0.04608394205570221,
0.0718354880809784,
-0.19321583211421967,
-0.5273398160934448,
0.0729093924164772,
0.2898719906806946,
1.163285493850708,
0.1733664870262146,
0.00920757744461298,
-0.6393190622329712,
-0.6792740225791931,
0.36454203724861145,
-0.48339638113975525,
0.5192394852638245,
... |
Definition: In this task, you are given an input list A. You need to find all the elements of the list that are numbers in the same order as they appear in the list A.
Input: ['Y', '9299', 'F', '187', '41', 'm', 'Z', '3293', '713', 'n', 'X']
Output: | 9299, 187, 41, 3293, 713 | 2 | NIv2 | task497_extract_all_numbers_from_list_in_order | zs_opt | [
-0.13991332054138184,
-0.0005886927247047424,
-0.566608190536499,
-0.8359608054161072,
-0.12147310376167297,
0.18370765447616577,
-0.08251030743122101,
-0.16687488555908203,
0.0739346593618393,
0.2899693548679352,
-0.7164020538330078,
0.007745692972093821,
-0.28818559646606445,
0.191149696... |
Q: You are given a sentence in Italian. Your job is to translate the Italian sentence into Galician.
I laser scansionano l'ambiente alla ricerca di ostacoli - una macchina che si avvicina da davanti o da dietro e anche gli eventuali ostacoli sulla strada, qualsiasi ostacolo presente intorno al veicolo.
A: | que examinan o entorno para detectar obstáculos: un coche acercándose por diante ou por detrás e calquera obstáculo que pode aparecer na carreteira, calquera obstáculo arredor do vehículo. | 7 | NIv2 | task1252_ted_translation_it_gl | zs_opt | [
-1.2516534328460693,
0.7248579263687134,
0.010809678584337234,
-0.1760055422782898,
-0.3460092544555664,
0.035518109798431396,
-0.2592741847038269,
0.7640676498413086,
0.7757318019866943,
0.37143129110336304,
-0.5164646506309509,
0.04279562458395958,
-0.06946496665477753,
0.245484352111816... |
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.
[EX Q]: លោក មៃឃើល ផាកខឺស ទាត់ចូលគ្រាប់ដំបូងមុនការបញ្ចប់ទឹកទីមួយ។
[EX A]: マイケル・パークハーストがハーフタイム直前に自陣からのゴールで初得点をあげた。
[EX Q]: សង្គមនេះបានលើកឡើងដ... | 乗組員は、飛行機をオヘア空港にまわし、飛行機を空にして、安全のために爆弾処理班が調べるのを受け入れることを決定した。
| 6 | NIv2 | task1122_alt_khm_ja_translation | fs_opt | [
0.22588887810707092,
-0.2521941065788269,
-0.9298685789108276,
-0.40987372398376465,
0.4291130006313324,
-1.3289401531219482,
0.608911395072937,
0.648673951625824,
-0.07159960269927979,
0.3806886374950409,
-0.657784640789032,
0.21098411083221436,
-0.5652995705604553,
0.3635159432888031,
... |
In this task, you're given a context passage, an answer, and a question. Your task is to classify whether the question for this answer is correct or not, based on the given context with commonsense reasoning about social situations. If its correct ,return "True" else "False".
Example input: Context: Tracy didn't go ho... | True | 3 | NIv2 | task384_socialiqa_question_classification | fs_opt | [
0.23500598967075348,
0.5930333137512207,
0.2769164741039276,
0.3793123662471771,
-0.021112944930791855,
-0.41169649362564087,
0.3288382887840271,
0.3784319758415222,
0.5021885633468628,
0.22288759052753448,
-0.5572605133056641,
-0.48294734954833984,
-0.049722231924533844,
-0.16532739996910... |
Detailed Instructions: In this task, you're given a question, along with three passages, 1, 2, and 3. Your job is to determine which passage can be used to answer the question by searching for further information using terms from the passage. Indicate your choice as 1, 2, or 3.
See one example below:
Problem: Question:... | 1 | 4 | NIv2 | task230_iirc_passage_classification | fs_opt | [
0.1166781336069107,
0.3675142824649811,
-0.5555216073989868,
0.10282739251852036,
0.5147865414619446,
-0.23790761828422546,
0.8446464538574219,
1.2966704368591309,
0.06668035686016083,
0.3101985454559326,
-0.08526664227247238,
0.2255876213312149,
-0.33518004417419434,
0.03015219047665596,
... |
In this task, you are given a sentence in Persian, and your task is to translate it into English.
اما در این صورت ممکن نیست که بگیم من مخصوصا برای نویسندگی ساخته نشدهام؟ | ;But then, may not I be peculiarly constituted to write? | 0 | NIv2 | task660_mizan_fa_en_translation | zs_opt | [
-0.5647515058517456,
0.8518043756484985,
0.8150953650474548,
0.7629832029342651,
-0.03232502192258835,
-0.3722838759422302,
-0.373688280582428,
0.2630959153175354,
0.6846283078193665,
-0.4317806363105774,
0.23203104734420776,
0.31804540753364563,
-0.1849055290222168,
0.14269022643566132,
... |
You will be given a definition of a task first, then some input of the task.
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 generative models have advanced the... | Unsupervised classification via deep generative modeling with controllable feature learning evaluated in a difficult real world task | 1 | NIv2 | task668_extreme_abstract_summarization | zs_opt | [
-0.7121343612670898,
-0.22127556800842285,
-0.49117785692214966,
-0.11939980089664459,
-0.40605300664901733,
-0.42299389839172363,
0.6103640794754028,
0.8199529647827148,
0.20205336809158325,
-0.10864423215389252,
-0.5830815434455872,
-0.00602745171636343,
-0.2999526858329773,
0.5734131336... |
Part 1. Definition
This task is about creating an unanswerable question based on a given passage. Construct a question that looks relevant to the given context but is unanswerable. Following are a few suggestions about how to create unanswerable questions:
(i) create questions which require satisfying a constraint that... | The five Great Lakes formal border with what country? | 7 | NIv2 | task348_squad2.0_unanswerable_question_generation | fs_opt | [
0.8716135025024414,
0.1817511022090912,
-0.8597862124443054,
-0.5430434346199036,
-0.06307460367679596,
-0.267821729183197,
0.9422166347503662,
1.042196273803711,
-0.04432711750268936,
0.12432704865932465,
-0.29387524724006653,
0.10610534995794296,
-0.9387092590332031,
0.16817110776901245,... |
Q: In this task, you are given a short passage that conveys a stereotype or an anti-stereotype. A stereotype is an over-generalized belief about a particular group of people(based on race, ethnicity, gender, age, abilities, etc.). An anti-stereotype is an idea that goes against a common stereotype. You are expected to ... | Anti-stereotype | 7 | NIv2 | task316_crows-pairs_classification_stereotype | zs_opt | [
-0.36480361223220825,
0.09745575487613678,
-0.3050466477870941,
0.18897002935409546,
-0.02160138264298439,
-0.09916730225086212,
1.0023386478424072,
0.6764504313468933,
0.6094331741333008,
-0.5219425559043884,
-0.8572089672088623,
0.35904884338378906,
-1.1192402839660645,
-0.10576131939888... |
Q: Your task is to generate the next utterance in a given dialogue. You will be given a few sentences describing the personality of the person who is making the dialogue, and a history of the dialogue after that. Each line in the history is said by one of the two participants in the conversation.
Personality: I grew up... | What is your favorite food? I make a mean homemade pizza. | 7 | NIv2 | task1729_personachat_generate_next | zs_opt | [
-0.35145899653434753,
0.04874899238348007,
-0.6107950210571289,
-0.1474885642528534,
-0.2208976149559021,
0.05163757875561714,
0.18855690956115723,
0.35689809918403625,
0.10390444099903107,
0.07202666997909546,
0.6047952175140381,
0.33077096939086914,
-0.6727334260940552,
-0.11576723307371... |
In this task you will be given a list of integers. You should remove any integer that is not prime. A prime integer is an integer that is only divisible by '1' and itself. The output should be the list of prime numbers in the input list. If there are no primes in the input list an empty list ("[]") should be returned.
... | [419, 241, 653, 397]
| 5 | NIv2 | task366_synthetic_return_primes | fs_opt | [
-0.7038916349411011,
0.12127116322517395,
-0.4393177032470703,
-0.5905299186706543,
-0.38479119539260864,
-0.12619590759277344,
0.6027284264564514,
0.5421379804611206,
-0.6159734725952148,
0.4235423505306244,
-1.4164769649505615,
-0.19085846841335297,
0.00874285027384758,
-0.82812261581420... |
You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Arabic.
Q: De modo que ese tornillo que vieron con anterioridad puede, actualmente, ser usado para soldar un hueso fracturado y para administrar fármacos al mismo tiempo, mientras el hueso se repara, por ejemplo.
A: | وبالتالي ذلك البرغي الذي فكرتم فيه سلفا يمكن في الواقع استعماله لربط عظمة مع بعضها البعض — عظمة مكسرة مع بعضها البعض — وإيصال العقاقير في نفسها ، بينما تشفى العظمة ، على سبيل المثال. | 4 | NIv2 | task1228_ted_translation_es_ar | zs_opt | [
-0.3096729516983032,
1.282132625579834,
0.3615361452102661,
-0.21361175179481506,
0.23495149612426758,
-0.6553382873535156,
0.6558939814567566,
1.3753983974456787,
0.26377683877944946,
-0.27210068702697754,
-0.05865863710641861,
1.0155155658721924,
-0.1319764256477356,
0.6837314367294312,
... |
In this task you will be given a list of integers. You should find the maximum absolute difference between 2 integers in the list. The absolute difference is the absolute value of one integer subtracted by another. The output should be a single integer which is the largest possible absolute distance.
Q: [97, 80, -25]
... | 151
****
| 4 | NIv2 | task1446_farthest_integers | fs_opt | [
-0.6148781776428223,
0.5430437326431274,
0.1912480890750885,
-0.5731642246246338,
-0.38953930139541626,
0.13377335667610168,
0.5852750539779663,
0.41833826899528503,
0.6679524183273315,
-0.10027655214071274,
-0.2626647353172302,
-0.07468222081661224,
-0.49359217286109924,
0.028526540845632... |
In this task, we have Spanish and Catalan tweets for automatic stance detection. The data has three labels Against, Favor, and Neutral which express the stance towards the target -independence of Catalonia. If the tweet criticizes the independence of Catalonia then it's 'Against' and if the tweets support it then it wi... | Neutral
****
| 4 | NIv2 | task1646_dataset_card_for_catalonia_independence_corpus_text_classification | fs_opt | [
0.5463982820510864,
0.041431911289691925,
-0.21912281215190887,
-0.02642112970352173,
0.27163660526275635,
-1.0358588695526123,
0.7230391502380371,
1.0930581092834473,
0.33925971388816833,
0.5028835535049438,
-0.6894153952598572,
0.5706629157066345,
0.03967709839344025,
-0.0527077093720436... |
You are given two sentences. You have to find if there is entailment or agreement of the Hypothesis by the Premise. From the given pair of sentences, you should identify if there is enough information in the Premise to support the claim made in the Hypothesis. The Premise may not exactly be the same as Hypothesis. Your... | neutral | 0 | NIv2 | task1529_scitail1.1_classification | zs_opt | [
-0.47896477580070496,
1.0480537414550781,
0.18231099843978882,
-0.08198332786560059,
-0.3973279595375061,
-1.0362091064453125,
0.5149303078651428,
0.37028247117996216,
0.13628718256950378,
-0.04216032475233078,
-0.8318116068840027,
0.19017945230007172,
-0.41454267501831055,
-0.234238386154... |
We would like you to assess the QUALITY of each of the following argument (discussing Gay Marriage) and determine if the argument is Valid or Invalid. A valid argument is clearly interpretable and either expresses an argument, or a premise or a conclusion that can be used in an argument for the topic of gay marriage. A... | Valid | 0 | NIv2 | task148_afs_argument_quality_gay_marriage | zs_opt | [
0.30639582872390747,
0.6154762506484985,
0.7228682041168213,
0.06703734397888184,
-0.19937370717525482,
-1.5676589012145996,
0.5221081376075745,
0.45084038376808167,
0.23944172263145447,
-0.03479999676346779,
-0.6399508714675903,
-0.2896779179573059,
-0.4462934732437134,
-0.143703460693359... |
Part 1. Definition
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.
Part 2. Example
Alphonse feels anxious.
Answer: fear
Expla... | joy | 7 | NIv2 | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | fs_opt | [
-0.1799071878194809,
0.20071116089820862,
0.29387176036834717,
-0.5175610184669495,
0.0645938366651535,
-0.3368298411369324,
1.3181636333465576,
0.2799578905105591,
0.29788103699684143,
-0.4495413303375244,
-0.7456216812133789,
-0.23672014474868774,
-0.6095384359359741,
-0.2183610051870346... |
Teacher: Given the sentence, generate "yes, and" response. "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line of thought or context ("and..."). 1 In short, a "Yes, and" is a dialogu... | I know. Wait until we exit through the gift shop. | 2 | NIv2 | task360_spolin_yesand_response_generation | fs_opt | [
0.5766075253486633,
0.9483455419540405,
0.34325212240219116,
0.2323416918516159,
0.11601467430591583,
-1.299185037612915,
0.30167004466056824,
0.7086935043334961,
-0.2375563383102417,
-0.40243250131607056,
-0.5739176273345947,
-0.010453522205352783,
-0.7076189517974854,
0.2034434676170349,... |
Teacher:You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Hebrew.
Teacher: Now, understand the problem? Solve this instance: Há três dicas importantes.
Student: | שלוש גישות עיקריות. | 6 | NIv2 | task1278_ted_translation_pt_he | zs_opt | [
-0.3690173327922821,
0.20689576864242554,
-0.04735831916332245,
-0.575218677520752,
-0.4189131557941437,
-0.1003260463476181,
0.9894765019416809,
-0.16065172851085663,
0.494240403175354,
-0.08356236666440964,
-0.4787333607673645,
-0.24715015292167664,
-0.7388166189193726,
-0.49861323833465... |
In this task you're given two statements in Marathi. You must judge whether the second sentence is the cause or effect of the first one. The sentences are separated by a newline character. Output either the word 'cause' or 'effect' .
मुलगी तिच्या पालकांची परवानगी इच्छित.
तिने तिच्या पालकांचे नियम पाळले. | effect | 0 | NIv2 | task943_copa_mr_commonsense_cause_effect | zs_opt | [
0.012275668792426586,
0.6443670988082886,
-0.01997540146112442,
-0.6344316601753235,
-0.8189363479614258,
-0.11389590799808502,
0.3659207820892334,
0.7509284615516663,
0.18495826423168182,
-0.7829440832138062,
-0.929684579372406,
-0.2588501572608948,
-0.5692147016525269,
-0.120623782277107... |
Given the task definition and input, reply with output. In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ).... | Yes | 5 | NIv2 | task1198_atomic_classification_owant | zs_opt | [
0.044054239988327026,
0.4763772487640381,
0.41046446561813354,
0.012028960511088371,
-0.3092573881149292,
-0.5348458290100098,
1.276329755783081,
0.1109345406293869,
-0.5992377400398254,
-0.4311879873275757,
-0.4188734292984009,
-0.2776568830013275,
-0.722174882888794,
0.22968542575836182,... |
Detailed Instructions: In this task, you're given reviews from Amazon's products. Your task is to generate the Summary of the review.
Problem:I found it on the big side. Also, I wasn't a big fan of the different modes. Only one of them felt good but it was a mode that changed rhythm every few seconds, so, not helpful. ... | Only one of them felt good but it was a mode that changed rhythm every ... | 8 | NIv2 | task618_amazonreview_summary_text_generation | zs_opt | [
0.10893192887306213,
0.2454221099615097,
-0.6117048263549805,
-0.5089803338050842,
-0.04994580149650574,
0.15900228917598724,
0.6397926807403564,
0.5503027439117432,
-0.3128696382045746,
0.5831606388092041,
-0.26412469148635864,
-0.16579686105251312,
-0.28899532556533813,
-0.32955700159072... |
Teacher: In this task, you're given the title of a five-sentence story and the first four sentences. Your job is to write the last sentence of the story to not connect with the rest of the story. Ensure that the generated sentence is contextually relevant to the story.
Teacher: Now, understand the problem? If you are s... | Dana's girlfriend screamed after Charles, you can't drive our car! | 2 | NIv2 | task215_rocstories_incorrect_answer_generation | fs_opt | [
-0.16917172074317932,
0.543850302696228,
0.3267139196395874,
-0.24806401133537292,
0.07015899568796158,
0.13356931507587433,
0.18093815445899963,
0.8208059072494507,
-0.0021969107910990715,
0.05142168328166008,
-0.5435083508491516,
-0.22622071206569672,
-0.28348666429519653,
-0.14774045348... |
Given a sentence in the Japanese, provide an equivalent translation in Thai that retains the same meaning through the translation. In translation, keep numbers as it is.
[EX Q]: カナダにあるもう一つのミクロネーションであるヴァイクランド公国のグランドプリンスクリストファー1世とエリン王女が出席する。
[EX A]: เจ้าชายคริสโตเฟอร์ ที่หนึ่ง และเจ้าหญิงเอริน จากราชรัฐไวส์แลนด์ประเทศจำ... | ในขณะเดียวกันอเมริกาได้เผยแพร่เอกสารซึ่งยังไม่สมบูรณ์ ระบุว่าทางการทหารอเมริกาได้ทำการสอบสวนร่วมกับทางเจ้าหน้าที่อิตาลีเพิ่อเคลียร์ว่าทหารของอเมริกาไม่มีส่วนเกี่ยวข้องและจะไม่แสดงความรับผิดชอบเกี่ยวกับเหตุการณ์น่าสลดที่เกิดขึ้นในวันที่ 4 มีนาคม
| 6 | NIv2 | task1127_alt_ja_th_translation | fs_opt | [
-0.304595947265625,
-0.2987208962440491,
-0.531993567943573,
-0.664449155330658,
-0.1709277629852295,
-0.3791462182998657,
0.7663782835006714,
0.8688020706176758,
-0.5208761692047119,
0.07439447194337845,
-0.25683408975601196,
0.3733798563480377,
-0.5173119306564331,
0.29146915674209595,
... |
Definition: In this task, you have to generate the named entities (NER) given its ingredients of the recipe. Named entities are the names of the items without their quantity.
Input: 2 cups all-purpose flour, 2 teaspoons cornstarch, 1 teaspoon baking soda, 3/4 cup butter, softened (if using margarine, use the stick type... | flour, cornstarch, baking soda, butter, brown sugar, sugar, egg, vanilla, white chocolate chips, almonds | 2 | NIv2 | task570_recipe_nlg_ner_generation | zs_opt | [
0.2442665994167328,
0.5416671633720398,
0.21703067421913147,
0.461389422416687,
-0.27678409218788147,
0.12727168202400208,
0.5605629682540894,
0.5811363458633423,
-0.3270531892776489,
-0.04858282953500748,
-0.20034246146678925,
-0.2571345567703247,
-0.7666300535202026,
-0.7309467792510986,... |
The task is to write a full sentence or two using all of the information given. The sentence(s) will be a brief review of a restaurant. Use all of the information provided.
Example input: name[xname], cuisine[Fast Food], rating[average], familyFriendly[yes], near[xnear]
Example output: Located near xnear, xname serves... | xname in Riverside, is kids-friendly, offers Italian food in the moderate price range near xnear. | 3 | NIv2 | task1598_nyc_long_text_generation | fs_opt | [
-0.5643905997276306,
0.6899458169937134,
-1.0408822298049927,
-0.5485522747039795,
-0.6398996114730835,
-0.30451852083206177,
1.0990253686904907,
0.8024682998657227,
0.22032278776168823,
-0.8006906509399414,
0.36232322454452515,
0.05824664607644081,
-0.30449068546295166,
0.0480582267045974... |
In this task you will be given a list, of lists, of integers. For every inner list contained in the input list, you should multiply every even number in that list. The output should be a list of integers with the same length as the number of lists in the input list. If there are no even numbers in an inner list you sho... | [300, 104, 957600, -8, 25344, 40, -50] | 8 | NIv2 | task851_synthetic_multiply_evens | fs_opt | [
-0.01855175942182541,
0.11904323846101761,
-0.6937680244445801,
0.0015368724707514048,
0.38481271266937256,
-0.4914552569389343,
1.138900637626648,
0.3353501558303833,
-0.40284717082977295,
-0.25692451000213623,
-0.7539525032043457,
0.12318987399339676,
-0.35358548164367676,
-0.54350280761... |
Detailed Instructions: 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.
Problem:Context: Examine the role of food spending behaviors and perceptions on fruit and vegetable intake among preadolescen... | Public health efforts to raise awareness of the relatively low cost of fruits and vegetables should be continued. These efforts may be complemented with policy strategies that make fruits and vegetables more viable options for low-income households. | 8 | NIv2 | task849_pubmedqa_answer_generation | zs_opt | [
0.5771855115890503,
-0.3377620577812195,
-0.545897364616394,
-0.24199993908405304,
-0.6533523797988892,
0.3662461042404175,
0.7160440683364868,
1.0903862714767456,
0.09394612163305283,
-0.2478499412536621,
-0.1605755090713501,
-0.12937715649604797,
-1.2046804428100586,
0.252909392118454,
... |
In this task, you are given a sentence. You must judge whether a single noun or verb has been replaced with another word with the same part of speech. The inversion would result in the sentence sounding unnatural, So unnatural sentences will be considered changed. Label the instances as "Original" or "Changed" based on... | Changed | 0 | NIv2 | task515_senteval_odd_word_out | zs_opt | [
-0.9883544445037842,
0.9341148734092712,
0.289298951625824,
-0.0003124247887171805,
-0.14941062033176422,
-0.18694835901260376,
0.34695589542388916,
1.0242412090301514,
0.4070313274860382,
-0.38286373019218445,
-0.9819899201393127,
-0.5338922142982483,
-1.1286996603012085,
-0.2567555010318... |
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 determ... | Yes | 6 | NIv2 | task1213_atomic_classification_desires | fs_opt | [
-0.14988704025745392,
0.24738307297229767,
0.5647673606872559,
-0.4359658360481262,
-0.6010695099830627,
-0.3189140558242798,
1.1758267879486084,
0.2242625504732132,
-0.5238986015319824,
-0.4935029447078705,
-0.593662679195404,
-0.3770849406719208,
-0.3180331289768219,
0.2674866318702698,
... |
Given the task definition and input, reply with output. In this task, you are given an input list A. You need to find all the elements of the list that are numbers and calculate their sum.
['A', '283', '9375', 'y', '6629', 'd', 'M', '1499', 'f', 'A', 'F']
| 17786 | 5 | NIv2 | task499_extract_and_add_all_numbers_from_list | zs_opt | [
-0.18248681724071503,
0.33239418268203735,
-0.23469530045986176,
-1.386559009552002,
-0.17033708095550537,
-0.04231473058462143,
0.12980632483959198,
-0.20136669278144836,
-0.13686826825141907,
-0.22124195098876953,
-1.2516874074935913,
0.31279808282852173,
0.212530717253685,
-0.5119180083... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence and a question in the input. If the information provided in the sentence is enough to answer the question, label "Yes", otherwise label "No". Do not use any facts other than those provided in the sentence while labelin... | Yes. | 1 | NIv2 | task050_multirc_answerability | zs_opt | [
-0.4594174921512604,
0.33872517943382263,
-0.3565466105937958,
0.5661953687667847,
-0.09567110985517502,
-0.928634524345398,
0.6493982076644897,
0.9406964778900146,
0.4960089921951294,
-0.029879262670874596,
-0.24127595126628876,
-0.1541084498167038,
-0.29861748218536377,
-0.39211675524711... |
In this task, you're given a review from Amazon and category of the product based on the review given by the user and your task is classify whether the given category match the review. Generate "True" if given review and its category match, otherwise generate "False".
Example Input: Reviews: Did not work at all. Have ... | False
| 3 | NIv2 | task1308_amazonreview_category_classification | fs_opt | [
0.1959550380706787,
0.6662155985832214,
-0.42712873220443726,
-0.5075318813323975,
-0.2018977403640747,
-0.37912067770957947,
0.7766295075416565,
0.556523323059082,
-0.21939073503017426,
0.003620737697929144,
0.4200890064239502,
0.3354833126068115,
-0.37114232778549194,
-0.1016720309853553... |
Given a sentence, generate a new 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.
--------... | You are uncommon to find a poster in a bedroom .
| 7 | NIv2 | task413_mickey_en_sentence_perturbation_generation | fs_opt | [
-0.32993850111961365,
0.4837348461151123,
-0.2633221447467804,
0.09949059039354324,
0.16130051016807556,
-0.657529354095459,
0.16506575047969818,
0.6133711338043213,
-0.6641323566436768,
-0.21099109947681427,
-0.3648463487625122,
-0.04127821326255798,
-0.8082405924797058,
0.356786131858825... |
instruction:
In this task, you need to answer the given multiple-choice question on the gain. Gain is the value by which to multiply the input. Classify your answers into 'a', 'b', 'c', 'd', and 'e'.
question:
Problem: a , b and c invested rs . 8000 , rs . 4000 and rs . 8000 respectively in a business . a left after si... | a
| 9 | NIv2 | task1419_mathqa_gain | fs_opt | [
0.31783899664878845,
0.42318451404571533,
-0.3900616466999054,
0.204523503780365,
-0.21113227307796478,
0.4063943028450012,
0.3218890130519867,
0.6559267044067383,
-0.18140555918216705,
0.1238480806350708,
-0.32155996561050415,
0.028264082968235016,
-0.38879305124282837,
-0.262669444084167... |
In this task, you need to count the number of words in a sentence that start with the given letter. Answer with numbers and not words.
Example Input: Sentence: 'five giraffes meandering along in their outdoor habitat'. How many words start with the letter 'f' in the sentence.
Example Output: 1
Example Input: Sentence... | 1
| 3 | NIv2 | task162_count_words_starting_with_letter | fs_opt | [
-0.41846561431884766,
0.4558219313621521,
0.08543149381875992,
-0.4807875454425812,
0.29267698526382446,
-0.6019477248191833,
-0.047063976526260376,
0.6918679475784302,
-0.18520936369895935,
-0.4993540644645691,
-1.0057907104492188,
0.008615135215222836,
-1.1174428462982178,
-0.20092698931... |
Definition: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Input: We use the pre-trained uncased BERT$_\mathrm {BASE}$ model for fine-tuning, because we find that BERT$_\mathrm {LARGE}$ model performs sli... | small BERT | 2 | NIv2 | task460_qasper_answer_generation | zs_opt | [
-0.26277804374694824,
0.9351252317428589,
-0.7241849303245544,
-0.17201043665409088,
-0.41685351729393005,
0.08315065503120422,
0.5061675310134888,
0.2023051232099533,
0.4850473701953888,
-0.30079901218414307,
-0.7112072706222534,
0.6332270503044128,
-0.10280242562294006,
0.178679436445236... |
Given a post that is a real-life anecdote of a complex ethical situation and an associated claim about its type, verify if the claim is true or not. The claim asks if the posts are historical or hypothetical. The posts are "HISTORICAL" when the author has already done something and they are "HYPOTHETICAL" when the auth... | no | 4 | NIv2 | task501_scruples_anecdotes_post_type_verification | zs_opt | [
0.0007612789049744606,
-0.050130654126405716,
-0.05901993066072464,
-0.06672708690166473,
0.3716123700141907,
-0.6568195819854736,
0.13076737523078918,
1.2745883464813232,
-0.20409393310546875,
-0.2686883211135864,
-0.07689067721366882,
0.7250463962554932,
-1.0371859073638916,
-0.250276952... |
Part 1. Definition
In this task, you are given a context and four options. Each option is a suggested ending for the context. You should read the context and pick the best ending for the context. Please answer with "A", "B", "C", and "D".
Part 2. Example
[header] How to create a christmas tree forest [title] Consider ... | B | 7 | NIv2 | task1389_hellaswag_completion | fs_opt | [
0.6784485578536987,
0.5247809290885925,
-0.6120057106018066,
-0.11504878103733063,
-0.05313970148563385,
-0.3350678086280823,
0.9955626130104065,
0.7216222286224365,
-0.04837600886821747,
0.08257102221250534,
-0.18820667266845703,
-0.08088890463113785,
-0.22278830409049988,
-0.175016924738... |
Detailed Instructions: 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 sent... | I had never ridden before but I was excited. That day, Jen was so happy, up on her horse. I smiled as I rode next to her. | 9 | NIv2 | task269_csrg_counterfactual_story_generation | zs_opt | [
0.71672523021698,
0.19591554999351501,
-0.101104736328125,
0.21044932305812836,
-0.1481451839208603,
-0.7399649620056152,
-0.2638697624206543,
1.4746825695037842,
-0.08136332035064697,
-0.6162359118461609,
-0.4994707703590393,
-0.27745288610458374,
-0.03528093174099922,
0.190656378865242,
... |
Teacher: The given sentence contains a typo which could be one of the following four types: (1) swapped letters of a word e.g. 'niec' is a typo of the word 'nice'. (2) missing letter in a word e.g. 'nic' is a typo of the word 'nice'. (3) extra letter in a word e.g. 'nicce' is a typo of the word 'nice'. (4) replaced let... | coyple | 2 | NIv2 | task088_identify_typo_verification | fs_opt | [
-0.5971702337265015,
0.47164440155029297,
-0.028491757810115814,
0.5035481452941895,
0.18507561087608337,
-1.1519650220870972,
0.4962833523750305,
0.5974072813987732,
0.0046003651805222034,
-0.01814449019730091,
-0.17400504648685455,
-0.367005318403244,
-0.4403280019760132,
-0.625579953193... |
Instructions: You are given a math word problem and you are supposed to apply multiplication or division mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Input: Wendy was playing a video game where she scores 5 points for each t... | 35 | 3 | NIv2 | task866_mawps_multidiv_question_answering | zs_opt | [
0.10660773515701294,
0.44800272583961487,
-0.30236515402793884,
-0.04531317204236984,
-0.31057071685791016,
0.17246046662330627,
0.786588191986084,
0.5929953455924988,
-0.23045556247234344,
-0.44845104217529297,
-0.3373567461967468,
-0.7178921699523926,
0.040837932378053665,
-0.20374827086... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a short story consisting of exactly 5 sentences where the second sentence is missing. You are given two options and you need to select the one that best connects the first sentence with the rest of the story. Indica... | Option 1 | 1 | NIv2 | task065_timetravel_consistent_sentence_classification | zs_opt | [
-0.35972321033477783,
0.5936592221260071,
-0.45185327529907227,
-0.6340857148170471,
-0.3443269729614258,
0.17206591367721558,
0.8014947175979614,
0.29504913091659546,
0.27493447065353394,
-0.6523723602294922,
-0.47931182384490967,
-0.9598696827888489,
-0.3066391050815582,
-0.2656352818012... |
instruction:
In this task, you are given a sentence in the English language and your task is to convert it into the Japanese language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
question:
Lebanon's defence minister, Elias Murr, says that t... | アメリカ東部標準時間の午前11時45分までに、オバマは349票の選挙人票を獲得し、マケインの163票に対して勝つと予想された。
| 9 | NIv2 | task435_alt_en_ja_translation | fs_opt | [
-0.14290925860404968,
0.10209432989358902,
0.15150171518325806,
-0.19280409812927246,
-0.023363791406154633,
-0.2347724437713623,
0.48176029324531555,
0.45453011989593506,
0.3199807405471802,
0.18240779638290405,
-0.7084358930587769,
0.2911645174026489,
-0.9130028486251831,
0.1464286446571... |
Part 1. Definition
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Part 2. Example
Sentence 1: Next to the MGM Grand you will find M and M World... | 4 | 7 | NIv2 | task198_mnli_domain_classification | fs_opt | [
-0.38572418689727783,
-0.20403754711151123,
0.4067268967628479,
-0.12444254755973816,
0.24520307779312134,
0.1365465372800827,
0.013367658481001854,
0.9752744436264038,
-0.029366131871938705,
-0.004352828953415155,
-0.5028199553489685,
-0.4291163980960846,
-0.09434901177883148,
-0.43045932... |
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 public comment from online platforms. You are expected to classify the comment into two classes: identity-attack and non-identity-attack. Identity attack refers to anyth... | Identity-attack | 0 | NIv2 | task325_jigsaw_classification_identity_attack | fs_opt | [
-0.1914091259241104,
0.23584264516830444,
0.44989073276519775,
0.2666545510292053,
-0.09170988202095032,
0.5872002840042114,
1.1472787857055664,
0.4940774440765381,
0.7051301002502441,
0.5668445825576782,
0.4389892816543579,
-0.28569838404655457,
-0.3154664635658264,
-0.5600874423980713,
... |
Definition: In this task, you need to remove all words of a given length in the sentence. The number of letters in a word determine its length, for example, the length of the word "apple" is 5.
Input: Sentence: 'one picture shows andy warhol with a banana to his face the other image shows a woman holding a banana to he... | one picture shows andy warhol with a banana his face the other image shows a woman holding a banana her ear | 2 | NIv2 | task377_remove_words_of_given_length | zs_opt | [
0.3545808792114258,
0.24007979035377502,
0.08749911189079285,
-0.3657798171043396,
0.07196405529975891,
-0.4493587613105774,
0.16663727164268494,
0.5066664814949036,
0.12035501003265381,
-0.43567878007888794,
-0.7601268291473389,
0.04047724977135658,
-0.5123023986816406,
0.2217073738574981... |
Detailed Instructions: Given a paragraph about cooking, and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversat... | Yes | 4 | NIv2 | task1439_doqa_cooking_isanswerable | fs_opt | [
-0.027736708521842957,
-0.007497918792068958,
-0.34645572304725647,
-0.00810929760336876,
0.24448645114898682,
-0.6038029193878174,
0.9173389673233032,
0.9749994277954102,
-0.40681642293930054,
0.36933743953704834,
0.1828186810016632,
0.15231254696846008,
-0.5749413967132568,
0.59646576642... |
In this task, you are given a text from tweets. Your task is to classify given tweet text into two categories: 1) positive, and 2) negative based on its content.
@flyfiddlesticks Spymaster is a crappy twitter based spy game
positive
I have a headache
negative
Damn it! Now it really came off
| negative
| 0 | NIv2 | task195_sentiment140_classification | fs_opt | [
-1.703869104385376,
0.00015834096120670438,
0.16983437538146973,
-0.15377330780029297,
0.2977343797683716,
-0.7789766788482666,
0.49580198526382446,
0.8856008052825928,
0.6749026775360107,
1.138938307762146,
-0.5927683115005493,
-0.1923218071460724,
-0.6331692934036255,
-0.9178556799888611... |
Detailed Instructions: In this task, you are given a context tweet, a question and corresponding answer of given question. Your task is to classify given passage into two categories: (1) "yes" if the given context is useful in answering the question, and (2) "no" if the given context is not useful.
See one example belo... | no | 4 | NIv2 | task242_tweetqa_classification | fs_opt | [
-0.5441726446151733,
0.22264301776885986,
0.6156808137893677,
-0.27643507719039917,
0.4306833744049072,
-0.14273688197135925,
0.01661103218793869,
0.8903592228889465,
0.0917050689458847,
0.12362825870513916,
-0.5219167470932007,
-0.37294551730155945,
-0.3031419515609741,
0.0579230561852455... |
In this task, you are given an answer, and your task is to generate a reasonable question for that answer.
One example: My stomach will be upset if i eat that.
Solution is here: Do you like pineapple on your pizza?
Explanation: The answer given was regarding something that the person ate and it caused his stomach upset... | Have you enough money to afford this flat ? | 6 | NIv2 | task568_circa_question_generation | fs_opt | [
-0.10116316378116608,
0.3101749122142792,
0.2761409878730774,
0.14700102806091309,
-0.01867365464568138,
-0.05988422781229019,
0.790777325630188,
0.2970570921897888,
-0.11523998528718948,
-0.1797548234462738,
-0.3076723515987396,
0.15234830975532532,
-1.1630009412765503,
0.0708047896623611... |
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 translation, keep numbers as it is.
Input: In agreeing to preside over the meeting of the Mohammedan Anglo-Oriental Educational Conference , then , Badruddin was clearly tempted by the... | मोहम्मडन एंगलों ओरिएंटल एजुकेशनल कांफ्रेंस की बैठक की अध्यक्षता स्वीकार करने में बदरूद्दीन के लिए स्पष्ट प्रलोभन यह था कि उनके सामने सामान्य तौर पर शिक्षा और विशेषकर लड़कियों की शिक्षा के प्रति , मुसलमानों के रवैये को बदलनें का अवसर था । | 3 | NIv2 | task425_hindienglish_corpora_en_hi_translation | zs_opt | [
0.0033585019409656525,
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-0.22626173496246338,
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-0.3026602864265442,
0.072097659111022... |
Detailed Instructions: In this task, you're given a question, along with a context passage. The passage will not have a direct answer to the question, but can include some information and a clue for the answer. Assuming you can only obtain information about one entity in the passage, your job is to determine whether in... | b | 8 | NIv2 | task233_iirc_link_exists_classification | zs_opt | [
0.18397322297096252,
-0.33682528138160706,
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0.21150171756744385,
0.1210799589753151,
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0.05576891452074051,... |
In this task, you're given the title of a story consisting of five sentences, numbered 1 through 5. Your job is to determine which two sentences need to be swapped sentences in order to make a story that makes complete sense and is befittingly titled. Indicate your answer using the numbers of the two sentences in order... | 12 | 4 | NIv2 | task218_rocstories_swap_order_answer_generation | zs_opt | [
-0.28265535831451416,
0.44579410552978516,
-0.146675705909729,
-0.9430873394012451,
-0.3280014991760254,
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0.5110312700271606,
0.5129735469818115,
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-0.9384241104125977,
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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 inputs i,j, and A, where i and j are integers and A is a list. You need to list all elements of A from the ith element to the jth element in the reverse order. i and j wil... | 9301, 9479, Q, i, M, 8017, R, 1985, 1043, S, j, 1653, 4957, b, 2955, 2915, 9819, T, Z, 7979 | 0 | NIv2 | task099_reverse_elements_between_index_i_and_j | fs_opt | [
0.012370701879262924,
0.2663043737411499,
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0.190139502286911,
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0.26405006647109985,
0.07996506243944168,... |
"Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line of thought or context ("and..."). Given a prompt and two responses, identify which response is the type of "yes, and". Indicate yo... | Response 1
| 3 | NIv2 | task362_spolin_yesand_prompt_response_sub_classification | fs_opt | [
0.42738276720046997,
0.5936893820762634,
0.06425350904464722,
0.3267625570297241,
0.5997214317321777,
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0.336712539196014... |
Q: Given a sentence in Dutch, generate a new Dutch sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it be... | Je hebt de overheid nodig om voedsel te kopen. | 7 | NIv2 | task409_mickey_nl_sentence_perturbation_generation | zs_opt | [
-0.6318812966346741,
0.989570140838623,
0.23671984672546387,
-0.28982245922088623,
-0.4613063931465149,
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0.347278356552124,
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0.788756251335144,
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0.45326846837997437,
... |
Q: Given an object and a part, decide whether the object has that part. For example is you are asked 'gun has barrel', you need to decide if a gun has a barrel as one of its components or parts. All sentences strictly follow the template 'object has part?.' The answer should be 1 or 0, 1 means the object has the given ... | 1 | 7 | NIv2 | task1584_evalution_meronym_classification | zs_opt | [
-0.48154646158218384,
0.3951559364795685,
-0.038548100739717484,
0.641092836856842,
0.2445376217365265,
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1.4001833200454712,
1.2107152938842773,
0.28087252378463745,
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-0.7355600595474243,
-0.253924161195755... |
Teacher:You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
Teacher: Now, understand the problem? Solve this instance: CA: 僕がビジネスを始めた頃ビジネスについて何もわかっていなくて CA: 僕がビジネスを始めた頃ビジネスについて何もわかっていなくてビジネスの世界の人間はただ冷徹にまたそうであることが成功への唯一の道だと思っていました
Student: | Cóż, Richard, gdy zaczynałem w biznesie nic o nim nie wiedziałem. Sądziłem, że biznesmeni muszą być bezwzględni i że tylko w ten sposób masz jakiekolwiek szanse na powodzenie. | 6 | NIv2 | task1097_ted_translation_ja_pl | zs_opt | [
-0.14675769209861755,
0.29857972264289856,
-0.0537990927696228,
-0.16859525442123413,
-0.11338221281766891,
-0.358009397983551,
0.00943140871822834,
0.39279723167419434,
-0.23731036484241486,
-0.29429614543914795,
-0.1183885782957077,
-0.4915706217288971,
-0.46237704157829285,
-0.601606905... |
In this task, you will be presented with a question in Dutch language, and you have to write the part-of-speech tag for each word and punctuation in the question. Here is the list of part-of-speech tags used in this task: Adj: Adjective, Adv: Adverb, Art: Article, Conj: Conjunction, Int: Interjection, N: Noun, V: Verb,... | Num N Punc N N Punc N Punc Punc | 8 | NIv2 | task1543_conll2002_parts_of_speech_tagging_answer_generation | fs_opt | [
-0.0031509159598499537,
0.9382124543190002,
-0.19285359978675842,
0.1675388514995575,
-0.18518009781837463,
-0.405897855758667,
0.6244850158691406,
-0.25302812457084656,
0.42360618710517883,
-0.36955174803733826,
-0.43878278136253357,
0.6043975949287415,
-0.5514481067657471,
-0.08154924213... |
Given a part of privacy policy text, identify the purpose for which the user information is collected/used. The purpose should be given inside the policy text, answer as 'Not Specified' otherwise
Let me give you an example: The site collects your IP address or device IDs for advertising. Collection happens when you im... | Marketing | 8 | NIv2 | task683_online_privacy_policy_text_purpose_answer_generation | fs_opt | [
-0.907367467880249,
-0.37201857566833496,
-0.5369701981544495,
0.05528781935572624,
-0.523110568523407,
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0.15378428995609283,
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-0.417277991771698,
0.9415395259857178,
0.40068426728248596,
-0.08964844048023224,
-0.26868394017219543,
-0.77084022760391... |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Portugese.
Example input: Ora, lungo il percorso, George segnala che la sua tecnologia, la tecnologia della biologia sintetica, sta accelerando molto più velocemente del tasso previsto dalla Legge di Moore.
Example output: Ao longo... | Agora vamos ver como funciona na prática. | 3 | NIv2 | task1255_ted_translation_it_pt | fs_opt | [
-0.43599528074264526,
1.0680299997329712,
-0.0014075231738388538,
-0.17570149898529053,
-0.10164398699998856,
-1.0643267631530762,
-0.9057283997535706,
1.6894657611846924,
-0.46270349621772766,
0.047013141214847565,
-0.7491996884346008,
0.3944203555583954,
-0.301463782787323,
-0.0990418270... |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a sentence in the English language and your task is to convert English sentence into the Gujarati language.
Example: A herd of sheep standing together grazing in a pasture.
Output: ઘેટાંની ટોળાં એક ગોચરમાં ચરાઈ સાથે... | એક ફેંગ પર ફેલાવાયેલો અને બેકગ્રાઉન્ડમાં સ્ટેટે | 1 | NIv2 | task438_eng_guj_parallel_corpus_en_gu_translation | fs_opt | [
-0.17331279814243317,
0.3855460286140442,
0.07748381793498993,
-0.13337069749832153,
0.11493003368377686,
-0.5279275178909302,
-0.3694625198841095,
0.3734065294265747,
-0.14654675126075745,
-0.4302517771720886,
-0.6579445600509644,
0.18085555732250214,
-0.43613389134407043,
-0.103980988264... |
Q: In this task, you are given a sentence from the Bible in Persian, and your task is to translate it into English.
زیرا خداوند طوایف بزرگ و زورآور را از پیش روی شما بیرون کرده است، و اما با شما کسی را تا امروز یارای مقاومت نبوده است.
A: | And Joshua called for all Israel, and for their elders, and for their heads, and for their judges, and for their officers, and said unto them, I am old and stricken in age: | 7 | NIv2 | task654_bible_fa_en_translation | zs_opt | [
-0.36002078652381897,
1.306376338005066,
-0.07830514758825302,
-0.19588106870651245,
-0.8828588128089905,
-0.09149844944477081,
0.4149673879146576,
0.5633894205093384,
0.2908955216407776,
-0.17187738418579102,
-0.2905573844909668,
0.516630232334137,
-0.617595911026001,
-0.2547823190689087,... |
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the q... | How many years were there between the end of the British Burma Campaign and the start of the Battle of Na San?
| 0 | NIv2 | task235_iirc_question_from_subtext_answer_generation | fs_opt | [
0.4238428473472595,
-0.2167283296585083,
-0.19924898445606232,
-0.8584429621696472,
-0.2373630702495575,
-0.3011511564254761,
0.5398859977722168,
0.298546701669693,
-0.24415093660354614,
0.4030354619026184,
-0.08747965097427368,
0.36791595816612244,
-1.1694773435592651,
0.42976561188697815... |
Given the task definition and input, reply with output. In this task, you will be given a short story. One sentence from the story is chosen. Consider the events that happen before that sentence, or are likely to have happened before it. Does any of them directly cause it, or simply make it possible? You should write y... | I ran out of toilet paper >Causes/Enables> We go to the store | 5 | NIv2 | task614_glucose_cause_event_detection | zs_opt | [
-0.33955538272857666,
1.0109901428222656,
-0.14458301663398743,
0.33486413955688477,
-0.1261320412158966,
-0.7110873460769653,
-0.21980145573616028,
0.9385765194892883,
0.27497804164886475,
-0.06984364986419678,
-0.6685316562652588,
0.0932057574391365,
-0.20135001838207245,
-0.304059982299... |
Definition: 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.
Input: Alrigh... | making my soccer teammate throw up | 2 | NIv2 | task500_scruples_anecdotes_title_generation | zs_opt | [
0.0921718031167984,
-0.27353933453559875,
-0.27609407901763916,
-0.5897983312606812,
0.15172886848449707,
-0.35397523641586304,
0.28008511662483215,
0.660186767578125,
-0.007435815408825874,
-0.0361563116312027,
-0.2669338583946228,
0.08796586096286774,
-0.8519516587257385,
-0.256860554218... |
In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: threat and non-threat. Threat is a statement that someone will be hurt or harmed, especially if the person does not do something in particular.
[EX Q]: Comment: Thanks for your kind words Phro... | Non-threat
| 6 | NIv2 | task322_jigsaw_classification_threat | fs_opt | [
-0.2509210705757141,
0.5798667669296265,
0.16038191318511963,
0.14491896331310272,
0.15782248973846436,
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0.8547964096069336,
1.052875280380249,
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0.5051361322402954,
0.2896825075149536,
0.707411527633667,
-1.0059059858322144,
-0.389298677444458,
-0... |
In this task, you're given reviews from Amazon's food products and a summary of that review. Your task is to classify whether the given summary matches the original review. Generate "True" if the given review and its summary match, otherwise generate "False".
Let me give you an example: Review: My cat won't touch thes... | False | 8 | NIv2 | task1309_amazonreview_summary_classification | fs_opt | [
-0.3692134618759155,
0.259750097990036,
-0.10511668771505356,
-0.2216883897781372,
-0.035782285034656525,
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0.1332128793001175,
0.6674975156784058,
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0.3080194592475891,
-0.30955392122268677,
0.27578240633010864,
-0.7450761795043945,
-0.175978988409042... |
Part 1. Definition
In this task, you are given a sentence in English, and your task is to translate it into Persian.
Part 2. Example
I heard enough of what she said to you last night to understand her unwillingness to be acting with a stranger;
Answer: دیشب شنیدم به تو چه میگفت. فهمیدم که دوست ندارد با یک غریبه این نق... | نگاهی هم به برادرش انداخت و اشارهای کرد و نگذاشت کسی از آن جمع تئاتری باز اصرار کند. | 7 | NIv2 | task661_mizan_en_fa_translation | fs_opt | [
0.47660452127456665,
1.3903937339782715,
-0.17455710470676422,
0.10484351217746735,
0.04879074543714523,
-0.5652308464050293,
1.333710789680481,
-0.027153287082910538,
0.3251897394657135,
-0.09756985306739807,
-0.1452142596244812,
0.27286145091056824,
-0.672734797000885,
-0.173201709985733... |
Detailed Instructions: 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 ef... | none | 8 | NIv2 | task1727_wiqa_what_is_the_effect | zs_opt | [
-0.23303654789924622,
0.3833898901939392,
-0.009808710776269436,
-0.7315882444381714,
-0.2659768760204315,
-0.5031172633171082,
0.5206184387207031,
0.6528010964393616,
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0.008890584111213684,
-0.010236169211566448,
-0.48253384232521057,
-1.0571198463439941,
0.13195243477... |
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