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 |
|---|---|---|---|---|---|---|
Given the task definition and input, reply with output. 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.
Bats are being increasingly recognized as reservoir hosts of high... | European Bats as Carriers of Viruses with Zoonotic Potential | 5 | NIv2 | task1161_coda19_title_generation | zs_opt | [
0.2337481528520584,
0.41056573390960693,
-0.5700193643569946,
0.6840043067932129,
-0.3342989981174469,
-0.5855072140693665,
-0.23624776303768158,
0.7336933612823486,
-0.07754875719547272,
0.16110488772392273,
-0.5919762849807739,
1.0074214935302734,
-0.8263425827026367,
-0.2649076879024505... |
In this task you will be given a list of numbers and you should remove all duplicates in the list. If every number is repeated in the list an empty list should be returned. Your list should be numbers inside brackets, just like the given list.
Q: [4, 6, 1, 5, 4, 2]
A: | [6, 1, 5, 2] | 4 | NIv2 | task097_conala_remove_duplicates | zs_opt | [
0.05478121340274811,
0.6644816398620605,
-0.3080355226993561,
-0.4095759391784668,
-0.17302590608596802,
-0.43653348088264465,
1.1976094245910645,
-0.6171185374259949,
-0.7259386777877808,
-0.21162503957748413,
-1.28082275390625,
-0.2649962306022644,
-0.2234136164188385,
-0.324382156133651... |
In this task you will be given a text passage from a trivia quiz. You should choose the category this question belongs to from these categories: History, Science, Social Science, Fine Arts, Literature. You can only choose one category, so if in doubt, please choose the closest match.
One example is below.
Q: In one wor... | Social Science | 9 | NIv2 | task521_trivia_question_classification | fs_opt | [
0.3052087128162384,
0.6835426688194275,
0.1566697657108307,
0.24096712470054626,
0.23097510635852814,
-0.07256537675857544,
0.510226309299469,
0.27536168694496155,
0.4088059961795807,
0.03657950088381767,
-0.520569920539856,
0.5284370183944702,
-0.9899592399597168,
-0.2592545449733734,
0... |
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: Answering a question regarding the issue, she said that... | 彼はまた、映画製作についての本、「インディ映画製作の最前線の物語」を記した。
| 7 | NIv2 | task435_alt_en_ja_translation | fs_opt | [
-0.18967804312705994,
-0.5578652620315552,
0.5263710021972656,
-0.015548553317785263,
0.3540981411933899,
0.6154002547264099,
0.5398596525192261,
0.2127026617527008,
-0.21205689013004303,
0.1651688814163208,
0.22106590867042542,
0.0778304859995842,
-0.9960557818412781,
-0.38910815119743347... |
You will be given a definition of a task first, then some input 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 will be non-negative, and will always have a va... | 6231, z, 5839, h | 1 | NIv2 | task099_reverse_elements_between_index_i_and_j | zs_opt | [
-0.2925005555152893,
0.07718662917613983,
-0.44849610328674316,
0.14375731348991394,
0.12271212041378021,
-0.14247195422649384,
0.4355557858943939,
-0.5672434568405151,
-0.1144973635673523,
0.23705586791038513,
-1.0593438148498535,
0.10766221582889557,
0.12501592934131622,
0.01038455031812... |
In this task you are given a sentence. You must judge whether there exist two consecutive words within the sentence with flipped orders, that is, whether the sentence will make sense and be correct if the order of two consecutive words changes. Label the instances as "Inversion" or "Original" based on your judgment.
S... | Original
| 0 | NIv2 | task428_senteval_inversion | fs_opt | [
-0.822746217250824,
1.036825180053711,
0.12371288239955902,
-0.3719251751899719,
-0.09368611872196198,
0.4341302514076233,
0.4746983051300049,
0.5690239667892456,
0.6960686445236206,
-0.33054882287979126,
-0.8466619849205017,
-0.45105069875717163,
-0.4543951153755188,
-0.3388320505619049,
... |
Given the task definition and input, reply with output. In this task, you will be shown a Persian passage and a question, and you have to determine whether the question is answerable based on the passage or not. If the question is answerable, choose the "True" label, and if not select "False"
اِصفَهان شهری تاریخی در م... | False | 5 | NIv2 | task396_persianqa_classification | zs_opt | [
0.06756201386451721,
0.7217569351196289,
0.20394910871982574,
0.23348736763000488,
0.32890892028808594,
0.0922020971775055,
0.6568626165390015,
0.7970805168151855,
0.28752830624580383,
-0.45188024640083313,
-0.4870414733886719,
1.8174822330474854,
-0.8322362899780273,
-0.18232250213623047,... |
The task is to generate text based off of an event. For the given event, there will be a person who does the action in the event (usually PersonX). Your task is to write that persons intent behind doing the event, i.e. why did the person do that action.
Example Input: PersonX has PersonX's wits about PersonX
Example O... | to be helpful
| 3 | NIv2 | task1596_event2mind_text_generation_2 | fs_opt | [
-0.4148028790950775,
0.6638219356536865,
0.2504661977291107,
-0.1684696227312088,
-0.40272921323776245,
-0.4891779124736786,
0.5816813707351685,
0.22749444842338562,
0.31103622913360596,
-0.28224658966064453,
-0.27620428800582886,
-0.025614701211452484,
-0.5855644941329956,
0.0966911092400... |
In this task, you are given Yelp reviews. The task is to classify a review as "POSITIVE" if the overall sentiment of the review is positive or as "NEGATIVE" if the overall sentiment of the review is negative.
[EX Q]: I've only been here once after work one night, and the experience wasn't too good.\n\nI remember order... | POSITIVE
| 6 | NIv2 | task475_yelp_polarity_classification | fs_opt | [
-0.44862911105155945,
-0.36295974254608154,
-0.32594990730285645,
-0.1455962359905243,
0.658557653427124,
-0.21370476484298706,
0.8909790515899658,
0.7955343127250671,
0.0628432184457779,
-0.0615009143948555,
0.5783644914627075,
0.07560206949710846,
-0.22468462586402893,
0.3498873114585876... |
This task is about translating a given English language sentence to Yoruba language.
One example is below.
Q: While you should not share legal advice to others based on course content, you will develop a high level of expertise upon completion of this course.
A: Bí ó ti jẹ́ wí pé o kò leè fún ẹnikẹ́ni nímọ̀ràn ajẹmófin... | Ibi tó jẹ́ ojúkò àgọ́ ìṣẹ́niníṣẹ̀ẹ́ ní Ravensbrück tó ti wá di ibi tí wọ́n ń kó àwọn nǹkan ìṣẹ̀ǹbáyé sí ti ṣe ètò kan tí wọ́n máa fi hàn ní àwọn ìlú káàkiri. Àkọlé ètò náà ni “Wọ́n Fòfin De Àwọn Ẹlẹ́rìí Jèhófà, Wọ́n sì Ṣe Inúnibíni sí Wọn ní Àgọ́ Ìṣẹ́niníṣẹ̀ẹ́ Ravensbrück àti Láwọn Ilé Ẹ̀wọ̀n Míì ní GDR.” Àfihàn náà jẹ... | 9 | NIv2 | task1685_menyo20k_translation | fs_opt | [
-0.25706905126571655,
-0.19275948405265808,
-0.17271387577056885,
-0.4283166527748108,
-0.4250686764717102,
-0.0628286749124527,
0.5901814699172974,
0.7754917740821838,
0.15583448112010956,
-0.6489976644515991,
-0.013035014271736145,
0.4051873981952667,
-1.236802339553833,
0.51811361312866... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a review of a product in the Polish language. Your task is to classify the given product review into these three categories: 1) positive, 2)neutral, 3) negative based on its content.
Text: Te akumulatorki to ściema... | negative | 1 | NIv2 | task634_allegro_reviews_classification | zs_opt | [
-0.47502046823501587,
0.41578519344329834,
0.012884189374744892,
-0.3759884536266327,
0.5456845760345459,
-0.21515129506587982,
1.1427892446517944,
0.2552855610847473,
0.211221843957901,
0.39587342739105225,
-0.21291683614253998,
0.5995434522628784,
-0.36979371309280396,
-0.296154856681823... |
In this task, you are given an input list A. You need to find all the elements of the list that are alphabets in the same order as they appear in the list A. Do not change their case/capitalization.
['5987', 'n', '4815', '6377', 'Q', 'G', 'J', 'g', 'i', 'n', 'I', '8465', '7341', '5417', '257', '1467', 'l', '345', '286... | n, Q, G, J, g, i, n, I, l | 0 | NIv2 | task488_extract_all_alphabetical_elements_from_list_in_order | zs_opt | [
0.09377631545066833,
0.8184616565704346,
0.14713247120380402,
-0.5284080505371094,
-0.10063048452138901,
0.31294944882392883,
0.272709459066391,
-0.6910833120346069,
-0.6020867824554443,
0.03274743631482124,
-0.5192474722862244,
-0.6120443344116211,
-0.3604581952095032,
0.11736884713172913... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a review of movie. Your task is to classify given movie review into two categories: 1) positive, and 2) negative based on its content.
Please humour me if you will, for a minute while I read you the back of the ALL... | negative | 1 | NIv2 | task284_imdb_classification | zs_opt | [
0.31992480158805847,
0.5151983499526978,
-0.908562183380127,
0.37968260049819946,
0.47575312852859497,
-0.3847465515136719,
0.29343342781066895,
1.1948083639144897,
-0.23993581533432007,
-0.05206876993179321,
-0.46238887310028076,
0.21826133131980896,
-0.5167433619499207,
-0.30280029773712... |
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... | No | 4 | NIv2 | task1209_atomic_classification_objectuse | zs_opt | [
0.3320913314819336,
0.4049631953239441,
0.43975159525871277,
-0.19006070494651794,
-0.6652052402496338,
-0.6571067571640015,
1.2375333309173584,
0.3879391551017761,
-0.44090914726257324,
-0.5827006101608276,
-0.8387504816055298,
-0.37482914328575134,
-0.2941974699497223,
0.3096802234649658... |
In this task, you need to answer the given multiple-choice question on the physics. Classify your answers into 'a', 'b', 'c', 'd', and 'e'.
Problem: a jeep takes 3 hours to cover a distance of 440 km . how much should the speed in kmph be maintained to cover the same direction in 1 / 2 th of the previous time ?
Optio... | c
| 0 | NIv2 | task1422_mathqa_physics | fs_opt | [
-0.4720524549484253,
-0.1062186136841774,
0.023403314873576164,
-0.15140871703624725,
-0.29025501012802124,
0.08205339312553406,
-0.36299049854278564,
0.7151538729667664,
-0.3364604115486145,
-0.45410531759262085,
-0.3839370608329773,
0.18481379747390747,
0.09792551398277283,
-0.0696534812... |
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".
Reviews: Allergies are unique to each of us....I p... | False | 0 | NIv2 | task1308_amazonreview_category_classification | zs_opt | [
-0.6290692090988159,
0.2682167589664459,
0.26500171422958374,
-0.5424562692642212,
-0.06248386204242706,
-0.48425930738449097,
0.3122813105583191,
0.4626600742340088,
0.1723928451538086,
0.35100844502449036,
-0.45385968685150146,
0.20171815156936646,
-0.37182849645614624,
-0.19865569472312... |
TASK DEFINITION: Given a passage, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions t... | Does bRCAness predict resistance to taxane-containing regimens in triple negative breast cancer during neoadjuvant chemotherapy?
| 8 | NIv2 | task847_pubmedqa_question_generation | fs_opt | [
0.8823621869087219,
0.11903643608093262,
-0.4558732211589813,
0.07424601167440414,
0.3415464162826538,
-0.44967758655548096,
1.159045696258545,
0.44267112016677856,
0.4569077789783478,
0.002614094177260995,
-0.5360953211784363,
0.12222645431756973,
-0.19169031083583832,
0.40390849113464355... |
Instructions: 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 odd 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 odd numbers in an inner ... | [-609, -285, 1519, -3773, -627, 49, -1715, -13299, -2325, 0, -105] | 3 | NIv2 | task852_synthetic_multiply_odds | zs_opt | [
-0.25380218029022217,
0.31297117471694946,
-0.7673683166503906,
-0.2540324330329895,
0.051798321306705475,
-0.20964112877845764,
1.2580158710479736,
0.14049315452575684,
-0.3181542754173279,
-0.32092660665512085,
-1.3956924676895142,
-0.2666071355342865,
-0.36487314105033875,
-0.5360300540... |
Detailed Instructions: In this task you will be given a string that only contains single digit numbers spelled out. The input string will not contain spaces between the different numbers. Your task is to return the number that the string spells out. The string will spell out each digit of the number for example '1726' ... | 73208 | 9 | NIv2 | task1443_string_to_number | zs_opt | [
-0.5007836818695068,
1.5399200916290283,
-0.4245777726173401,
-1.2751433849334717,
-0.14726966619491577,
-0.5755438208580017,
0.8634124994277954,
0.13755913078784943,
-0.07325215637683868,
-0.4934992492198944,
0.05542084202170372,
0.6491174697875977,
-0.6924271583557129,
-0.374586641788482... |
Instructions: 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 crea... | They then cleaned up trash, folded up the blanket, and went home. | 3 | NIv2 | task071_abductivenli_answer_generation | zs_opt | [
-0.23297394812107086,
0.9392355680465698,
-0.10715538263320923,
-0.5437922477722168,
-0.7710222601890564,
-0.19596749544143677,
0.7805357575416565,
0.44443202018737793,
-0.12563374638557434,
-0.05898165702819824,
-0.49302947521209717,
0.33714383840560913,
-0.3709452748298645,
-0.1785911172... |
Detailed Instructions: Given a post that is a real-life anecdote of a complex ethical situation and a question asks if AUTHOR, NOBODY, EVERYBODY, or OTHER is wrong in the situation. Answer the question and classify your answers into yes or no.
Q: Is OTHER wrong in the post ? POST : Long story short I saw a couple kids ... | yes | 9 | NIv2 | task502_scruples_anecdotes_whoiswrong_verification | zs_opt | [
-0.1665584295988083,
0.03879363834857941,
0.120635986328125,
-0.32103195786476135,
-0.30136945843696594,
-0.9085712432861328,
0.4310843050479889,
0.9479987621307373,
0.35333335399627686,
0.23664727807044983,
-0.1286686360836029,
-0.38811546564102173,
-0.6633850932121277,
-0.407187104225158... |
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.
[EX Q]: The situation makes Ryan feel anxious.
[EX A]: fear
[EX Q]: Torranc... | fear
| 6 | NIv2 | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | fs_opt | [
-0.15182256698608398,
0.5408897399902344,
0.5505799055099487,
-1.0676968097686768,
-0.3265942931175232,
0.03930101916193962,
0.703437864780426,
0.5392821431159973,
-0.10316605120897293,
-0.21675890684127808,
-0.49791863560676575,
-0.5126757621765137,
-0.7425756454467773,
0.2237346470355987... |
Definition: 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".
Input: Bulgarian: (Se levanta la sesión a las 23.30 horas), English: Opening of the sitti... | no | 2 | NIv2 | task273_europarl_classification | zs_opt | [
-0.15983176231384277,
0.08510012924671173,
0.08746567368507385,
0.8381307125091553,
-0.27553778886795044,
-0.33919084072113037,
0.740904688835144,
-0.24888059496879578,
0.849136471748352,
-0.4337843954563141,
0.1328648328781128,
0.7596387267112732,
-0.6960164308547974,
0.6111199855804443,
... |
In this task, you will be shown a Persian passage and a question, and you have to determine whether the question is answerable based on the passage or not. If the question is answerable, choose the "True" label, and if not select "False"
[EX Q]: کاخ باکینگهام در لندن اقامتگاه اصلی خانواده سلطنتی بریتانیا است. این کاخ ... | True
| 6 | NIv2 | task396_persianqa_classification | fs_opt | [
1.1292142868041992,
0.8194282650947571,
-0.2276243269443512,
-0.2546232342720032,
0.2614695429801941,
-0.6331406235694885,
1.0554757118225098,
0.724956214427948,
0.15522347390651703,
0.5227600932121277,
-0.48073089122772217,
0.5586066246032715,
-1.1886576414108276,
0.11705683916807175,
-... |
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.
Q: ['9545', '2631', '3223', 'J', 'N', 'Y', 'j', 'd', 'p', '2587', 'J', '1009', '4689', 'c', '5729', 'E', '2159', '9515', 'G', 'h', 'o', '839', 'U', 'S', 'z', '7845'... | 9545, 2631, 3223, 2587, 1009, 4689, 5729, 2159, 9515, 839, 7845, 6211 | 4 | NIv2 | task497_extract_all_numbers_from_list_in_order | zs_opt | [
0.10127196460962296,
0.6466966867446899,
-0.6432417631149292,
-0.07282182574272156,
-0.2916150689125061,
-0.3527281582355499,
0.5665736198425293,
0.07132260501384735,
-0.5457489490509033,
0.886913537979126,
-0.6033436059951782,
-0.1935422718524933,
-0.06112059950828552,
0.00765006523579359... |
Given a sentence in the Japanese and Central Khmer language. Your task is check if the Khamer sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Q: Japanese: 2隻のカナダの軍艦と2機の空軍機、CC-138ツインオッタ—とCP-140オーロラが、カナダの北極での実習に参加した。
Khamer: កប៉ាល់កងទ័ពជើងទឹករ... | Yes | 4 | NIv2 | task1123_alt_ja_khm_answer_generation | zs_opt | [
-0.661780059337616,
-0.31285274028778076,
-0.49013450741767883,
-0.1660260260105133,
0.23655062913894653,
-0.8226275444030762,
0.20996394753456116,
0.2892606854438782,
-0.4713536202907562,
0.03405991941690445,
0.1598936915397644,
-0.4691793918609619,
-0.34957215189933777,
0.188058704137802... |
Detailed Instructions: In this task you will be given some text dialogue and you need to infer the underlying emotion of the text. The possible emotions are happy, sad, angry, or other.
Problem:you are very bad sorry tiredfacetiredface because you are sending other's message to me
Solution: | sad | 8 | NIv2 | task517_emo_classify_emotion_of_dialogue | zs_opt | [
-0.43206584453582764,
0.696077823638916,
0.5891405344009399,
-1.2048861980438232,
0.024019526317715645,
-0.8434407114982605,
0.6444612741470337,
0.2226683646440506,
0.6484525203704834,
0.04795249551534653,
-0.30445194244384766,
-0.6848423480987549,
-0.6732702851295471,
0.09325473755598068,... |
Detailed Instructions: Read the given sentence and if it is a general advice then indicate via "yes". Otherwise indicate via "no". advice is basically offering suggestions about the best course of action to someone. advice can come in a variety of forms, for example Direct advice and Indirect advice. (1) Direct advice:... | yes | 8 | NIv2 | task115_help_advice_classification | zs_opt | [
-0.05873476713895798,
0.14288204908370972,
-0.005351130850613117,
-0.035969119518995285,
0.28466495871543884,
-1.5098298788070679,
0.7452924847602844,
0.3568779230117798,
0.18819424510002136,
0.30953720211982727,
-0.31296873092651367,
-0.8740516901016235,
-0.5298214554786682,
0.09937030076... |
In this task, you're given a passage, 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 passage and link information to create the q... | What part of England was the area that produced fustian located in? | 0 | NIv2 | task236_iirc_question_from_passage_answer_generation | zs_opt | [
0.729299783706665,
0.9802343845367432,
-0.4007510542869568,
0.012563951313495636,
-0.3991296887397766,
-1.2862459421157837,
-0.33058443665504456,
1.2862467765808105,
-0.4281361997127533,
0.1562320441007614,
-0.6640591621398926,
0.7162987589836121,
-0.5444686412811279,
0.19756019115447998,
... |
Part 1. Definition
In this task, you're given four sentences of a story written in natural language. The given story is not complete and your job is to complete the story by selecting one of the end sentence choices from (A) and (B), such that the story does not sound complete and coherent, i.e., select an incorrect en... | A | 7 | NIv2 | task297_storycloze_incorrect_end_classification | fs_opt | [
0.5690261125564575,
0.22060726583003998,
-0.32785648107528687,
-0.28024449944496155,
0.5761065483093262,
-0.779355525970459,
0.8214881420135498,
0.8987446427345276,
-0.1930694282054901,
0.052370086312294006,
-0.7222598195075989,
-0.1362973302602768,
-0.5210296511650085,
-0.0685146823525428... |
Teacher:Given an entity as input, output another entity which is part of the input entity. These are entities of meronym. In linguistics, meronymy is a semantic relation between a meronym denoting a part and a holonym denoting a whole. In simpler terms, a meronym (i.e., output entity) is in a part-of relationship with ... | mucous membrane | 6 | NIv2 | task471_haspart_answer_generation | zs_opt | [
-0.6398796439170837,
0.40804585814476013,
0.33950090408325195,
0.01143385749310255,
-0.5126259326934814,
-0.13937193155288696,
-0.3702280521392822,
0.029994111508131027,
0.41626545786857605,
-1.189018964767456,
-0.7185053825378418,
-0.030377479270100594,
-0.5057516098022461,
0.051681265234... |
Definition: You will be given a context, a subject and a relation. Your task is to generate a question based on the subject and relation. The generated question should include the given subject. Try to use a minimum number of words that are not present in either context, subject or relation while generating question.
I... | Which place does Animal Ark exist in? | 2 | NIv2 | task1325_qa_zre_question_generation_on_subject_relation | zs_opt | [
-0.6973520517349243,
0.1243562176823616,
-0.49433621764183044,
0.20509320497512817,
-0.7432404160499573,
0.2963302731513977,
0.1534646898508072,
-0.30161988735198975,
-0.11799256503582001,
-0.39329591393470764,
-0.4312676191329956,
0.2533089518547058,
-1.082201361656189,
0.4239946603775024... |
In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Input: Consider Input: English: Oil has risen to a new all-time record high during ... | Output: No
| 2 | NIv2 | task437_alt_en_ja_answer_generation | fs_opt | [
-0.14595326781272888,
-0.8805066347122192,
0.22037413716316223,
0.40917468070983887,
0.3604522943496704,
-0.4979504644870758,
0.4314178228378296,
0.9887151718139648,
-0.8954969644546509,
0.23237471282482147,
0.3287031054496765,
0.20863324403762817,
-0.5426312685012817,
-0.031902976334095,
... |
Given a sentence and a label in Croatian, select the correct answer. There are 2 choices given, out of which only one is correct for a given statement and label. The label of the task is either 'cause' or 'effect'. The output will be the choice which matches the label with the given statement. If the label is 'cause', ... | Ocjene su mu se popravile. | 9 | NIv2 | task1626_copa_hr_question_answering | fs_opt | [
-0.19070535898208618,
0.40091484785079956,
-0.3590548038482666,
0.3599628806114197,
-0.4734035134315491,
-1.182018756866455,
-0.11722693592309952,
0.3978399634361267,
-0.23023131489753723,
0.010267653502523899,
-0.44525545835494995,
0.7474216222763062,
-1.0543184280395508,
-0.0846731066703... |
In this task, you're given an article, a question which often contains a blank and four options (associated with "A", "B", "C", "D"). Your task is to find the correct answer (from the given options) for the question from the given article and return one of the options from "A", "B", "C", and "D". Do not generate anythi... | C | 0 | NIv2 | task309_race_answer_generation | zs_opt | [
0.3142043352127075,
0.26939472556114197,
-0.1318282186985016,
-0.17139127850532532,
0.426133394241333,
-0.17968596518039703,
1.6127429008483887,
0.6504358649253845,
-0.09205086529254913,
0.15383100509643555,
-0.2780618667602539,
0.8349003791809082,
0.061840008944272995,
-0.0684202611446380... |
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: The officer, said to be in his 50s, is recovering in hospital following the incident at HMP Bedford on Saturday. The union said he had s... | A prison officer had emergency surgery after an inmate punched him and stamped on his head, the Prison Officers Association (POA) said. | 6 | NIv2 | task1357_xlsum_summary_generation | zs_opt | [
0.595452070236206,
0.12415720522403717,
-0.21034207940101624,
-0.6367379426956177,
0.5039328932762146,
-1.0580031871795654,
0.6251544952392578,
1.0899012088775635,
0.40961354970932007,
-0.11469145119190216,
-0.32992351055145264,
0.3899758756160736,
-0.3329097032546997,
0.36502957344055176,... |
Detailed Instructions: In this task, you will be given a set of steps that are required to answer a specific question. Your job is to generate that question. Each given step refers to either an entity (known or unknown), a propery of an entity or a query operation (count, group, union, etc.) Knowing those operations an... | what is the name of leonardo dicaprio and kate winslet's new movie? | 9 | NIv2 | task184_break_generate_question | zs_opt | [
0.5863567590713501,
0.12116093933582306,
-0.9028578996658325,
0.7073718309402466,
0.24129006266593933,
-0.4837084412574768,
0.8595361709594727,
0.35235321521759033,
-0.5137959718704224,
0.4942297339439392,
-0.3284631669521332,
0.19682684540748596,
-0.12207435071468353,
0.12544935941696167,... |
In this task, you will be presented with a text and a pronoun. You should write the name that the pronoun refers to. Position of the pronoun in the text is showed within two "_"s.
Q: But when Scorpius shows that he knows of Snape having been in love with Lily, Harry's mother - Snape's most closely guarded secret - Sna... | Bilbo
****
| 4 | NIv2 | task330_gap_answer_generation | fs_opt | [
0.4691983461380005,
0.9600054025650024,
-0.3505006432533264,
0.13786157965660095,
-0.48939862847328186,
-1.0060384273529053,
0.5295891761779785,
0.46691590547561646,
0.5525872707366943,
0.22826062142848969,
0.024392250925302505,
0.7590683102607727,
-1.0214396715164185,
-0.42491376399993896... |
Detailed Instructions: You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Japanese.
Problem:E o que descobriram é que mesmo quantidades minúsculas de petróleo e dispersantes podem ser altamente tóxicas para o fitoplâncton, o que são péssimas notícias, porque muita vida depende... | ほんの微量の原油や分散剤でも植物性プランクトンには非常に有害であることが調査で判明しましたこれはとても厄介な問題ですなぜなら非常に多くの生命が影響を受けるからです | 8 | NIv2 | task1275_ted_translation_pt_ja | zs_opt | [
-0.4261096119880676,
-0.04092906415462494,
-0.061923399567604065,
0.17107456922531128,
-0.2234010100364685,
-1.5288817882537842,
0.9635167121887207,
0.43165692687034607,
-0.3255482316017151,
-0.23271556198596954,
-1.000425100326538,
0.15195229649543762,
-0.9326700568199158,
-0.284359574317... |
Detailed Instructions: In this task, you are given an answer, and your task is to generate a reasonable question for that answer.
Q: Only one or two drinks.
A: | Can you drink? | 9 | NIv2 | task568_circa_question_generation | zs_opt | [
-0.16831523180007935,
1.517854928970337,
0.18048220872879028,
-0.7167667150497437,
-0.2807929813861847,
-1.448176622390747,
-0.1355265974998474,
0.2968047261238098,
0.37090229988098145,
-0.47133344411849976,
0.16501563787460327,
-0.880892813205719,
-0.9567900896072388,
-0.39385464787483215... |
Teacher:You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Polish.
Teacher: Now, understand the problem? Solve this instance: Y le dijo: "" No tuviste, hasta éste momento, verdadera compasión.
Student: | I dodał, "" Nie posiadałeś do tej chwili prawdziwego współczucia. | 6 | NIv2 | task1102_ted_translation_es_pl | zs_opt | [
-0.37494635581970215,
0.9948692917823792,
0.13193883001804352,
-0.6495698690414429,
-0.4436969459056854,
-0.4427300989627838,
0.7481839656829834,
0.1354251205921173,
0.22792990505695343,
0.00935805682092905,
0.532899022102356,
-0.09090763330459595,
-0.4803871512413025,
-0.05123089998960495... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to write a single word that describes the genre that the two sentences belong to, such as face-to-face, government, letters, 9/11, slate, telephone, travel, verbatim, oup, fiction.
Sentence 1: Bauerstein arrested for the murder of M... | fiction
| 0 | NIv2 | task197_mnli_domain_answer_generation | fs_opt | [
-1.1765140295028687,
0.7292983531951904,
0.3361162841320038,
-0.6433389186859131,
0.1999603807926178,
0.22156108915805817,
-0.00729148555546999,
0.9025965929031372,
0.08865320682525635,
0.06205243617296219,
-0.12243103981018066,
0.3982200622558594,
-0.2875244617462158,
-0.10041285306215286... |
Q: In this task, you are given a text which is the body of a document. Your job is to classify the topic of the document into these categories: 1)Company, 2)Educational Institution, 3)Artist, 4)Athlete, 5)Office Holder, 6)Mean of transportation, 7)Building, 8)Natural place, 9)Village, 10)Animal, 11)Plant, 12)Album, 13)... | 5 | 7 | NIv2 | task629_dbpedia_14_classification | zs_opt | [
-0.478721559047699,
0.6366746425628662,
0.0910467728972435,
0.5984137654304504,
0.017564833164215088,
-0.6634427309036255,
0.25541892647743225,
0.14299890398979187,
-0.1258605420589447,
0.005241433624178171,
-0.2921326756477356,
0.16202574968338013,
0.07333650439977646,
-0.3574119210243225... |
Given the task definition, example input & output, solve the new input case.
You are given a paragraph (Passage), a question (Question) and two answer options (Option1 and Option2). Your task is to choose the correct answer to the question based on the passage. Answer of the question cannot be found directly from the p... | After sweeping the floor | 1 | NIv2 | task165_mcscript_question_answering_commonsense | fs_opt | [
0.9914331436157227,
0.8398152589797974,
-0.7419660091400146,
0.5803037881851196,
0.12553828954696655,
-0.21655945479869843,
0.5002661943435669,
1.0214977264404297,
-0.5450045466423035,
0.020240753889083862,
0.03369366377592087,
0.015419449657201767,
0.04041808843612671,
-0.1237696483731269... |
Given a sentence and an entity, the task is to select the authors sentiment towards the enity. Sentiments can be Positive, Neutral and Negative. Select Positive if the sentence expresses a positive view towards the given entity or praises its quality or skills. Select Neutral if the sentence expresses no clear view tow... | Neutral | 3 | NIv2 | task421_persent_sentence_sentiment_classification | fs_opt | [
-0.8074467182159424,
0.09447772800922394,
0.5286112427711487,
0.128054678440094,
-0.1945076584815979,
-1.2672412395477295,
1.034776210784912,
0.36177879571914673,
0.6955962777137756,
0.2143125832080841,
0.008938442915678024,
0.5491868257522583,
-0.44675004482269287,
-0.20643238723278046,
... |
Q: In this task, you are given a sentence from the Quran in English, and your task is to translate it into Persian.
Truly man is, to his Lord, ungrateful;
A: | [که] قطعا انسان نسبت به پروردگارش بسیار ناسپاس است، | 7 | NIv2 | task656_quran_en_fa_translation | zs_opt | [
-1.2187557220458984,
1.8383030891418457,
0.526451826095581,
-0.8899547457695007,
-0.4924461245536804,
-1.002604603767395,
0.42095452547073364,
0.49243640899658203,
0.22086305916309357,
-0.35682517290115356,
-0.5882692337036133,
0.3949996829032898,
-0.8962807655334473,
0.07076554000377655,
... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given an input list A. You need to extract and sort the unique digits used in the list in ascending order. Return -1 if there is no digit in the list.
['z', '339', 't', '485', '147', 'g', '447', 'f', 'w', '423', '279', '... | 1, 2, 3, 4, 5, 7, 8, 9 | 1 | NIv2 | task637_extract_and_sort_unique_digits_in_a_list | zs_opt | [
-0.23114556074142456,
-0.21518203616142273,
-0.26523369550704956,
-0.2689739167690277,
0.6792007684707642,
0.43950894474983215,
0.6526317000389099,
-0.22241756319999695,
-1.052040696144104,
0.5109138488769531,
-0.5481458902359009,
-0.03566541522741318,
-0.5636210441589355,
-0.3738425076007... |
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 ev... | Yes | 4 | NIv2 | task1211_atomic_classification_hassubevent | fs_opt | [
0.31737983226776123,
0.18302632868289948,
0.13068529963493347,
0.18167142570018768,
-0.3609659671783447,
-0.8905713558197021,
0.9584298133850098,
0.7345083951950073,
-0.6240814924240112,
-0.058847296983003616,
-0.20515131950378418,
-0.3783031105995178,
-0.6064348816871643,
0.01459741778671... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Polish. Your job is to translate the Polish sentence into Galician.
Spędzamy dużą ilość czasu w budynkach, które stanowią bardzo ściśle regulowane środowiska, takie jak ten budynek tutaj — środowiska, które mają uk... | Pasamos unha cantidade enorme de tempo en edificios que son entornos extremadamente controlados, coma este mesmo; entornos que contan con sistemas de ventilación mecánica que inclúen filtrado, calefacción e aire acondicionado. | 1 | NIv2 | task1261_ted_translation_pl_gl | zs_opt | [
-0.5537526607513428,
1.1125946044921875,
-0.3755910098552704,
-0.6866391897201538,
-0.27395135164260864,
-1.399336576461792,
-0.2280104160308838,
0.18788424134254456,
-0.12251095473766327,
0.3687129616737366,
-0.0633259192109108,
-0.067714162170887,
-0.5940852165222168,
0.3217986226081848,... |
Given the task definition and input, reply with output. This task is about translating a given English language sentence to Spanish.
No. Chapoui? Already was there.
| No. - ¿A Chapoui? | 5 | NIv2 | task1691_qed_amara_translation | zs_opt | [
0.06984341144561768,
0.5822177529335022,
0.2987114191055298,
0.04418342188000679,
-0.5721209049224854,
-0.4214511513710022,
0.19343455135822296,
0.5536155104637146,
0.10149361938238144,
-0.6512728333473206,
-0.35249167680740356,
-0.10835858434438705,
-0.1846083104610443,
0.4150760769844055... |
Detailed Instructions: You will be given a context and a verb separated with a newline character. You have to identify if the given verb implies an opinion, an intention, a wish or not. Please note that a verb refers to an intention only if it refers to an event planned to happen in the future and is not conditional (o... | Yes | 9 | NIv2 | task456_matres_intention_classification | zs_opt | [
-0.682269275188446,
0.30279067158699036,
0.4061885476112366,
0.5261853933334351,
-0.18408703804016113,
-0.3567999005317688,
0.3217960596084595,
0.4103132486343384,
0.26010894775390625,
-0.0876733735203743,
0.4197535216808319,
-0.199302539229393,
-0.1892545521259308,
-0.036191798746585846,
... |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Portugese.
Example input: אחרי הכל, הם החליטו, והם עשו,
Example output: Afinal de contas elas é que decidem, e decidiram mesmo.
Example explanation: The Hebrew sentence is correctly translated into Portugese, because the meaning is p... | Certamente que é. | 3 | NIv2 | task1114_ted_translation_he_pt | fs_opt | [
0.3742173910140991,
1.1077337265014648,
0.4071784019470215,
0.30408617854118347,
-0.6137281656265259,
-1.1497869491577148,
0.3865019679069519,
0.6018927097320557,
0.6939934492111206,
-0.31414440274238586,
-0.35373255610466003,
0.6013141870498657,
-0.6368091106414795,
-0.04529571533203125,
... |
In this task, you're given a context, a question, and three options. Your task is to find the correct answer to the question using the given context and options. Also, you may need to use commonsense reasoning about social situations to answer the questions. Classify your answers into 'A', 'B', and 'C'.
One example: Co... | C | 6 | NIv2 | task580_socialiqa_answer_generation | fs_opt | [
0.7067024111747742,
0.5362902283668518,
0.025316452607512474,
0.37638264894485474,
0.10918882489204407,
-0.3351250886917114,
0.7123542428016663,
0.1866934895515442,
-0.22551319003105164,
0.3460705578327179,
-0.021518807858228683,
-0.03140116110444069,
0.0031384516041725874,
-0.926226496696... |
Classify the given tweet into the three categories: (1) 'Hate Speech', (2) 'Offensive' and (3) 'Neither'. 'Hate Speech' is kind of a threating statement or sometimes include call for violence while 'offensive' statement just offensds someone. 'Neither' is when it doesn't fall into Hate Speech or Offensive category.
Le... | Offensive | 8 | NIv2 | task904_hate_speech_offensive_classification | fs_opt | [
-0.5850415825843811,
0.42179185152053833,
0.5252392888069153,
0.3088683784008026,
-0.09436795860528946,
-0.8299989104270935,
-0.1939592957496643,
0.6530774235725403,
0.5405384302139282,
0.47410643100738525,
-0.17503151297569275,
-0.3354407548904419,
-0.7502655982971191,
-0.7501844167709351... |
Given an English language product review, determine if it is a Good Review or a Bad Review. A good review is one where the product's review has positive tone and Bad review is one where the tone of product's review is negative.
[Q]: I really liked this movie. The story was a little predictable but with time watching i... | Bad review
| 5 | NIv2 | task929_products_reviews_classification | fs_opt | [
-0.36359089612960815,
0.17895695567131042,
-0.3506135940551758,
0.19978289306163788,
0.5069025754928589,
-0.9084904789924622,
0.6634135246276855,
0.8219910264015198,
-0.4611715078353882,
0.29977527260780334,
0.04712073132395744,
0.4499496817588806,
-0.5360556840896606,
-0.1312820315361023,... |
Instructions: A text is given in Gujarati. Translate it from the Gujarati language to the Panjabi language. The translation must not omit or add information to the original sentence.
Input: ਰਾਸ਼ਟਰੀ ਫ਼ਿਲਮ ਪੁਰਸਕਾਰਾਂ ਦੀ ਸਿਲੈਕਸ਼ਨ ਇੱਕ ਨਿਰਪੱਖ ਅਤੇ ਸੁਤੰਤਰ ਜਿਊਰੀ ਰਾਹੀਂ ਕੀਤੀ ਜਾਂਦੀ ਹੈ ਜਿਸ ਵਿੱਚ ਉੱਘੇ ਫ਼ਿਲਮ ਨਿਰਮਾਤਾ ਅਤੇ ਫ਼ਿਲਮੀ ਹਸਤੀਆਂ ... | ફિલ્મ નિર્દેશકો અને જાણીતી ફિલ્મ હસ્તીઓનું બનેલું સ્વતંત્ર અને તટસ્થ નિર્ણાયક મંડળ રાષ્ટ્રીય ફિલ્મ પુરસ્કારો માટે દર વર્ષે એપ્રિલ મહિનામાં પસંદગીઓ કરે છે અને પછી તેની જાહેરાત થાય છે. | 3 | NIv2 | task1044_pib_translation_punjabi_gujarati | zs_opt | [
-0.4271470308303833,
0.21451878547668457,
0.16046053171157837,
0.6245870590209961,
-0.21877050399780273,
-0.48824238777160645,
0.14667299389839172,
-0.2501654624938965,
-0.9518950581550598,
0.3486352562904358,
-0.7715319395065308,
-0.7883641123771667,
-0.5880769491195679,
0.235478177666664... |
Part 1. Definition
Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the pass... | Does iron-limited condition modulate biofilm formation and interaction with human epithelial cells of enteroaggregative Escherichia coli ( EAEC )? | 7 | NIv2 | task845_pubmedqa_question_generation | fs_opt | [
0.48121368885040283,
0.3956163227558136,
-0.20411211252212524,
0.08567826449871063,
0.5796835422515869,
-0.5981283187866211,
0.3740515410900116,
0.7164413332939148,
-0.24220480024814606,
-0.0564592070877552,
-0.391218364238739,
0.18148896098136902,
-0.8597012162208557,
0.534795880317688,
... |
Definition: Given a sentence in English language, translate the sentence to Tagalog language keeping the meaning of the original sentence intact.
Input: English sentence: Who is made, not after the law of a carnal commandment, but after the power of an endless life. (Hebrews 7:16)
Output: | Na ginawa, hindi ayon sa kautusan ng utos na ukol sa laman, kundi ayon sa kapangyarihan ng isang buhay na walang katapusan. (Hebreo 7:16) | 2 | NIv2 | task448_opus_paracrawl_en_tl_translation | zs_opt | [
0.15053029358386993,
1.3469668626785278,
0.2168121337890625,
-0.13110774755477905,
-0.604377269744873,
-1.339279055595398,
1.0440059900283813,
0.324470579624176,
0.4284958243370056,
0.0876583680510521,
0.22904174029827118,
0.05987919867038727,
-1.2997841835021973,
0.20064768195152283,
-0... |
Teacher:In this task, you are given a sentence in either Spanish or English. Your task is to determine the language of the input sentence. Input sentences can only be in Spanish or English, and they cannot be in two languages at the same time.
Teacher: Now, understand the problem? Solve this instance: This is illustr... | English | 6 | NIv2 | task533_europarl_es-en_language_identification | zs_opt | [
-0.14037436246871948,
0.2905871272087097,
0.910330593585968,
-0.6567125916481018,
0.20505206286907196,
-0.8975851535797119,
-0.3555395007133484,
1.0071983337402344,
0.2952827215194702,
-0.40696460008621216,
0.052858635783195496,
-0.26981568336486816,
-0.05788407102227211,
-0.80636560916900... |
A text is given in Bengali. Translate it from the Bengali language to the Hindi language. The translation must not omit or add information to the original sentence.
Example: ইংরেজিতেও সবাই বলেন – পেসিমিজ্ম লীড্স টু উইক্নেস্, অপ্টিমিজ্ম টু পাওয়ার।
Example solution: हर किसी ने अंग्रेजी में भी कहा - पेस्मिज्म लीड्स... | Solution: आपने देखा होगा हमारे देश में सैन्य व्यवस्था, सैन्य शक्ति, सैन्य संसाधन - उसके Reorm पर लंबे अरसे से चर्चा चल रही है। | 5 | NIv2 | task1009_pib_translation_bengali_hindi | fs_opt | [
-0.11853912472724915,
0.3888643980026245,
0.01694842427968979,
-0.32635122537612915,
0.014614970423281193,
-1.227390170097351,
-0.009736848995089531,
-0.03180180490016937,
-0.09645453095436096,
-0.12702947854995728,
-0.5894620418548584,
0.0028500540647655725,
0.013227973133325577,
0.165542... |
Given a sentence in Somali language, translate the sentence to English language keeping the meaning of the original sentence intact
Example Input: Somali sentence: 30 waayo, waxay saas u noqotay Yaaraabcaam dembiyadiisii uu dembaabay, oo uu dadkii Israa'iilna dembaajiyey, iyo xanaaqii uu ka xanaajiyey Rabbiga ah Ilaah... | 5 And the sons of the prophets that were at Jericho came to Elisha, and said unto him, Knowest thou that the LORD will take away thy master from thy head to day? And he answered, Yea, I know it; hold ye your peace.
| 3 | NIv2 | task450_opus_paracrawl_so_en_translation | fs_opt | [
-0.05212351679801941,
0.5662398934364319,
0.16696566343307495,
-0.6997052431106567,
-0.011153995990753174,
-0.40756693482398987,
0.829299807548523,
1.0379343032836914,
0.30003032088279724,
-0.030101953074336052,
-0.41268959641456604,
1.7543880939483643,
-1.2687649726867676,
-0.883096456527... |
Q: You will be given a sentence that describes a restaurant. You will also be given a few categories of information regarding that sentence. Your task is to fill each of the categories with the appropriate information from the sentenece.
Sentence: I would recommend xname because xname offers good decor, bad service and... | cuisine[English], qual[acceptable], decor[good] | 7 | NIv2 | task1597_nyc_slot_filling | zs_opt | [
-0.7513766884803772,
0.8483033776283264,
-0.30465659499168396,
-0.4514228105545044,
-0.5955779552459717,
0.26048558950424194,
0.21365481615066528,
0.36409276723861694,
0.33104076981544495,
0.03805933892726898,
0.8959341645240784,
-0.46279188990592957,
-0.9709420204162598,
-0.02365256845951... |
Given the task definition, example input & output, solve the new input case.
You are given a sentence in Polish. Your job is to translate the Polish sentence into Galician.
Example: Dzisiaj, w Szwecji i innych bogatych krajach ludzie używają mnóstwo najróżniejszych urządzeń.
Output: Hoxe, en Suecia e outros países rico... | E logo, por suposto, hai charlas que son tan únicas que están como na estratosfera, no seu propio sitio especial, e a iso chamámoslle a lista Colleen Flanagan. | 1 | NIv2 | task1261_ted_translation_pl_gl | fs_opt | [
-1.0654098987579346,
0.8668250441551208,
-0.3513118624687195,
-0.615399956703186,
0.10327090322971344,
-0.08038858324289322,
0.671697735786438,
0.12825720012187958,
-0.16274116933345795,
-0.28437334299087524,
-0.21881404519081116,
0.6448673009872437,
0.2861044406890869,
-0.0654561072587966... |
Definition: 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, but are not the correct answer. Even though ... | CNN | 2 | NIv2 | task303_record_incorrect_answer_generation | zs_opt | [
0.4335973858833313,
0.4603726863861084,
0.6167916655540466,
0.1669236421585083,
0.035018861293792725,
0.4394807815551758,
1.0698516368865967,
0.6513137817382812,
0.5371295213699341,
-0.3253602385520935,
-0.42122459411621094,
0.40895533561706543,
-0.1201610341668129,
0.15685975551605225,
... |
In this task, you're expected to write answers to questions involving multiple references to the same entity. The answer to the question should be unambiguous and a phrase in the paragraph. Most questions can have only one correct answer.
[EX Q]: Passage: Bryant identified "Son of Three" as an example of "when the Bre... | van Eyck.
| 6 | NIv2 | task002_quoref_answer_generation | fs_opt | [
0.29501116275787354,
0.08469152450561523,
-1.0333408117294312,
-0.11836358159780502,
-0.03947671130299568,
-0.13565894961357117,
1.3091506958007812,
0.32252806425094604,
-0.3474210500717163,
0.6532933712005615,
-0.4226292073726654,
0.4259672462940216,
-0.11205198615789413,
-0.1919589042663... |
In this task, you are provided with an article of the legal acts. Your task is to classify it into three categories (Regulation, Decision and Directive) based on its content: 1) Regulation is a binding legislative act that must be applied in its entirety on a set date across all the member states (European Union countr... | Directive | 4 | NIv2 | task744_eurlex_classification | zs_opt | [
-0.2657907009124756,
0.6562511920928955,
0.15004006028175354,
-0.3193323612213135,
-0.06828407198190689,
0.02398056536912918,
0.6638368964195251,
0.2526876926422119,
-0.2694122791290283,
0.14824774861335754,
-0.5877639651298523,
0.33871227502822876,
0.08914794772863388,
-0.2691474556922912... |
You will be given a definition of a task first, then some input 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 into many different actions. Actions are upperc... | I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_RIGHT I_TURN_RIGHT I_TURN_RIGHT I_TURN_RIGHT | 1 | NIv2 | task126_scan_structured_text_generation_command_action_all | zs_opt | [
0.30201613903045654,
0.6737138032913208,
-0.40732812881469727,
0.27810901403427124,
0.16506026685237885,
0.04071371257305145,
0.2424544095993042,
0.25247323513031006,
-0.22190441191196442,
-0.45343855023384094,
-0.8053275346755981,
-0.4882051944732666,
-0.48677170276641846,
-0.175175011157... |
In this task you will be given a list of integers. You should remove all of the integers that are divisible by 3 from the list. If every integer in the input list is divisible by 3 then an empty list should be returned. Zero is divisible by 3.
One example is below.
Q: [2, 5, 9, 6, 11]
A: [2, 5, 11]
Rationale: 6 and 9 a... | [53, -64, -83, -97, -22] | 9 | NIv2 | task370_synthetic_remove_divisible_by_3 | fs_opt | [
-0.10999021679162979,
-0.022081676870584488,
-0.05843710899353027,
-0.8485135436058044,
0.2377706617116928,
-0.3221820890903473,
0.6304913759231567,
0.10627952218055725,
-0.2494429647922516,
0.263113796710968,
-0.7273998260498047,
-0.12069431692361832,
0.03354866802692413,
-0.4008415937423... |
In this task, you are given a context paragraph, a question based on that and corresponding answer of a question. Your task is to generate supporting fact/knowledge from context paragraph which helps in answering a given question.
Example Input: Krzysztof Eugeniusz Penderecki ( ; ] ; born 23 November 1933) is a Polish... | It is a collection of 20 songs from Deicides catalogue with Roadrunner Records, the label with whom the band had recently ended its careerlong record deal.
| 3 | NIv2 | task192_hotpotqa_sentence_generation | fs_opt | [
0.32390546798706055,
0.5427880883216858,
-0.5902419090270996,
0.565220832824707,
0.04991814121603966,
-0.4989882707595825,
0.8100067973136902,
0.4121011197566986,
-0.09882308542728424,
0.6656908988952637,
-0.04556281864643097,
0.48600974678993225,
-0.48449814319610596,
0.13670091331005096,... |
instruction:
In this task, you will be shown a conversation and a question. You need to answer the question and choose the correct option based on the conversation. "W" and "M" in the conversations stand for "woman" and "man".
question:
M: Parcel Express, good morning! How can I help you? W: Good morning. I'm thinking ... | (B) Be relaxed and calm and she will make it.
| 9 | NIv2 | task247_dream_answer_generation | fs_opt | [
0.17404375970363617,
0.042591460049152374,
-0.3789207935333252,
-0.2594485878944397,
0.6508166790008545,
-0.4891735017299652,
0.7571975588798523,
0.641477644443512,
0.014798972755670547,
0.12794062495231628,
-0.31480956077575684,
0.29373234510421753,
0.4396517276763916,
0.23636336624622345... |
Detailed Instructions: Generate a topic word for the given sentence. A topic word is usually the name of a person, place, animal, concept or object the sentence is focusing on.
Problem:dame may whitty (also known as mary louise whitty; june 19, 1865 – may 29, 1948) was an english actress.
Solution: | may whitty | 8 | NIv2 | task645_summarization | zs_opt | [
0.452698677778244,
0.3732457756996155,
-0.059511084109544754,
-0.21947163343429565,
0.471439927816391,
-0.8461077213287354,
-0.6520649790763855,
-0.296427845954895,
0.5846796631813049,
-0.08459403365850449,
-0.378684937953949,
-0.3781610131263733,
-0.18209698796272278,
0.1557977795600891,
... |
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... | 1
| 3 | NIv2 | task200_mnli_entailment_classification | fs_opt | [
0.7472424507141113,
-0.29515203833580017,
-0.9342132806777954,
0.631759524345398,
-0.07735908031463623,
-0.9448306560516357,
0.40808987617492676,
1.5524373054504395,
-0.14745497703552246,
0.010469386354088783,
-0.8339594602584839,
0.3095424473285675,
-0.39190903306007385,
-0.21431739628314... |
Detailed Instructions: You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following:... | No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,No emotion | 9 | NIv2 | task1532_daily_dialog_emotion_classification | zs_opt | [
-0.18467679619789124,
-0.10886459052562714,
-0.03861500322818756,
-0.00849197432398796,
0.005476503632962704,
-0.3723517656326294,
0.32728391885757446,
-0.24383966624736786,
0.38985466957092285,
-0.1239188015460968,
-0.2113456279039383,
-0.2980058789253235,
-0.11797668039798737,
0.04515790... |
Definition: In this task, you are given a dialogue between a user and an assistant, where users and assistants converse about geographic topics like geopolitical entities and locations. The task here is to find if the dialogue is by the user or assistant. Classify your answers into user and assistant.
Input: In 2007, I... | assistant | 2 | NIv2 | task577_curiosity_dialogs_classification | zs_opt | [
-0.2828751504421234,
0.7870698571205139,
-0.35392022132873535,
-0.5505511164665222,
-0.7170017957687378,
0.5788325071334839,
1.0005650520324707,
-0.3015902042388916,
1.1440237760543823,
-0.1331346482038498,
-0.3096908926963806,
-0.1815042793750763,
-0.37021803855895996,
0.05514190346002579... |
Teacher:Given a comment text in Tamil, classify the comment into one of these categories (i) Hope speech, if it contains encouraging, positive or supportive contents about equality, diversity or inclusion, (ii) Not Hope Speech or (iii) Not in Expected Language, if the text is not Tamil.
Teacher: Now, understand the pro... | Hope Speech | 6 | NIv2 | task680_hope_edi_tamil_text_classification | zs_opt | [
-0.4992657005786896,
0.08069945871829987,
0.7605529427528381,
0.061355531215667725,
-0.09107192605733871,
-0.943773627281189,
-0.2862466275691986,
0.9757593274116516,
-0.6747583746910095,
0.36149466037750244,
-0.09530971199274063,
0.29680976271629333,
-0.04894626885652542,
-0.7877678871154... |
In this task, you are given a pair of action statements. Your task is to check if you can conclusively identify which statement is less ethical or not. Answer: 'no' if one of the statements is less ethical, and 'yes' otherwise.
--------
Question: ACTION1: cutting someone off ACTION2: not donating to a funeral Go-Fund-m... | yes
| 7 | NIv2 | task508_scruples_dilemmas_more_ethical_isidentifiable | fs_opt | [
-0.37692752480506897,
0.31908515095710754,
0.34308382868766785,
0.23454639315605164,
-0.27569007873535156,
-0.8046690821647644,
0.12808124721050262,
0.738834798336029,
-0.23536953330039978,
0.5278862118721008,
-0.20136573910713196,
-0.5800855159759521,
-0.6857951283454895,
-0.6584475636482... |
Teacher:In this task, You are given an amazon food product review and its summary. Your task is to Generate "True" if given review and its summary match, otherwise generate "False".
Teacher: Now, understand the problem? Solve this instance: Having always been a strict Peet's Coffee lover, I was reticent to switch brand... | True | 6 | NIv2 | task590_amazonfood_summary_correction_classification | zs_opt | [
-0.3503900468349457,
-0.4897213578224182,
-0.019695430994033813,
-0.6350699663162231,
-0.1394236981868744,
-0.7763621807098389,
0.5454006195068359,
-0.06281781196594238,
-0.24847516417503357,
-0.11395964026451111,
0.2132682502269745,
-0.3306616246700287,
-0.4344704747200012,
-0.55354619026... |
Given the task definition, example input & output, solve the new input case.
In this task, you need to Translate Czech text to English.
Example: Řešení se týká herbicidů a regulátorů růstu rostlin, obzvláště herbicidů pro selektivní potírání plevelů v kulturách užitkových rostlin. Konkrétně se týká nových acylovaných a... | The present invention relates to a screw for mutual fastening of at least two components (2, 3), comprising a shank (4) having a free end and an axis (9), the shank (4) being provided with a thread (6) extending over at least a portion of its length, and also comprising a screw head (5), wherein an unthreaded shank (4)... | 1 | NIv2 | task842_para_pdt_cs_en_translation | fs_opt | [
-0.2884228229522705,
0.06170393526554108,
0.06981456279754639,
0.11537113040685654,
0.10342445969581604,
-0.49526989459991455,
0.022037742659449577,
0.7831239104270935,
0.3820570409297943,
-0.1296166479587555,
-0.7627514600753784,
0.334486722946167,
-0.3763405680656433,
-0.1191638857126236... |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: political or non-political depending on the top... | political | 9 | NIv2 | task1491_bengali_political_hate_speech_binary_classification | fs_opt | [
-0.32545146346092224,
0.08943846821784973,
0.4296427369117737,
0.4273451566696167,
-0.5257183909416199,
-0.6024265289306641,
0.3552846312522888,
0.20259302854537964,
-0.32073110342025757,
0.012989631853997707,
-0.6739345192909241,
-0.03661689907312393,
0.10310660302639008,
-0.4454394578933... |
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.
[50, 118, 2... | [21] | 0 | NIv2 | task205_remove_even_elements | zs_opt | [
-0.40954917669296265,
0.4242616891860962,
-0.058753155171871185,
-0.7046995162963867,
0.34798669815063477,
-0.265809565782547,
1.1579889059066772,
0.3597857356071472,
-0.3826152980327606,
0.4783852696418762,
-0.8549340963363647,
0.21585172414779663,
-0.4477633535861969,
-0.4767870008945465... |
In this task you will be given a text passage from a trivia quiz. You should choose the category this question belongs to from these categories: History, Science, Social Science, Fine Arts, Literature. You can only choose one category, so if in doubt, please choose the closest match.
The third led a revolt based in Br... | History | 0 | NIv2 | task521_trivia_question_classification | zs_opt | [
0.021745283156633377,
0.25540289282798767,
0.17995771765708923,
-0.9301536083221436,
-0.12481087446212769,
-0.007584027945995331,
-0.4982193112373352,
0.6281998157501221,
0.15630444884300232,
-0.2612144351005554,
-0.32197266817092896,
0.0009205660317093134,
-0.4036383628845215,
-0.72449338... |
Definition: In this task, you will be presented with a text and a pronoun. You should write an implausible answer to the question of what is the pronoun's reference. Even though there exist multiple wrong answers, we only need a single wrong answer. Position of the pronoun in the text is showed within two "_"s.
Input: ... | Theresa | 2 | NIv2 | task331_gap_incorrect_answer_generation | zs_opt | [
-0.23145973682403564,
1.118887186050415,
0.09314075112342834,
0.27481094002723694,
-0.1881965696811676,
-0.15329179167747498,
1.1317033767700195,
0.6433969736099243,
0.799992561340332,
-0.18404322862625122,
-0.4346644878387451,
0.15621311962604523,
-0.6192449331283569,
0.004716949537396431... |
Detailed Instructions: 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".
See one example belo... | True | 4 | NIv2 | task384_socialiqa_question_classification | fs_opt | [
-0.05520717799663544,
0.4344820976257324,
0.2173222154378891,
0.347556471824646,
-0.2228357493877411,
-0.20288491249084473,
0.5140957832336426,
0.7408571839332581,
0.3460289239883423,
0.2713318467140198,
-0.7196415662765503,
-0.32921546697616577,
-0.14509564638137817,
0.22439783811569214,
... |
Detailed Instructions: You will be given a text in Russian language which contain different emotion labels from the list - ['joy', ' sadness', 'surprise', 'fear', 'anger']. You need to output the incorrect emotion label, which is irrelevant to the input text. Your answer (i) should contain only one emotion label (ii) s... | anger | 9 | NIv2 | task1663_cedr_ru_incorrect_classification | zs_opt | [
-0.6481576561927795,
-0.06708942353725433,
-0.12075021117925644,
-0.5032246112823486,
-0.5771210193634033,
-0.5704019069671631,
0.38601598143577576,
0.9274365901947021,
0.15485027432441711,
-0.453483521938324,
-0.2950669229030609,
-0.13788394629955292,
-0.3520523011684418,
-0.1677495539188... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Polish. Your job is to translate the Polish sentence into Farsi.
A to jeden ze sposobów na przekazanie jej tam.
Output: | و این راهی بود که موسیقی به آنجا راه پیدا کرد | 1 | NIv2 | task1263_ted_translation_pl_fa | zs_opt | [
-0.3461172580718994,
1.096176028251648,
-0.04055498540401459,
-0.06468091160058975,
-0.3710540533065796,
0.3168814182281494,
1.1258655786514282,
-0.017579276114702225,
0.5336196422576904,
0.3067857623100281,
-0.6807126998901367,
0.34180453419685364,
-0.10963128507137299,
0.4525069296360016... |
You are given a sentence in Persian. Your job is to translate the Farsi sentence into Portugese.
Ex Input:
هر روز باید برایش مبارزه کنید
Ex Output:
É preciso lutar por ela diariamente.
Ex Input:
بالای سرمون رو نگاه میکنن وقتی ما روی زمین راه میریم بالای سرمون رو نگاه میکنن وقتی ما روی زمین راه میریم
Ex Output:
Vêe... | Vamos discutir isso daqui a pouco.
| 1 | NIv2 | task1273_ted_translation_fa_pt | fs_opt | [
-0.6711347103118896,
0.45624399185180664,
-0.08104094117879868,
0.4764653742313385,
-0.45323827862739563,
-0.3084612488746643,
-0.08400409668684006,
0.5990347266197205,
0.0333157442510128,
0.1492888480424881,
-1.1519522666931152,
-0.08581706881523132,
0.022842559963464737,
0.12790903449058... |
instruction:
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
question:
Tweet: @theTpain I couldn't go! I had no ride ... | yes
| 9 | NIv2 | task196_sentiment140_answer_generation | fs_opt | [
-1.5417659282684326,
0.07117822766304016,
0.2240593135356903,
0.24709197878837585,
-0.19193314015865326,
-0.8046918511390686,
0.35356688499450684,
0.203607976436615,
0.10450340807437897,
0.28294217586517334,
-0.5094101428985596,
0.08627380430698395,
0.13265487551689148,
-0.3403044939041137... |
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: Coordi... | False
| 7 | NIv2 | task346_hybridqa_classification | fs_opt | [
-0.2745167016983032,
0.3270123600959778,
-0.565241813659668,
0.36983823776245117,
-0.7202532291412354,
-0.8023800253868103,
0.9609593152999878,
0.8809192180633545,
-0.29012471437454224,
0.1433209478855133,
-1.0711628198623657,
0.7463647723197937,
-0.3081028163433075,
-0.023147448897361755,... |
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.
Ex Input:
પ્રધાનમંત્રીએ આયુષ્માન ભારત હેઠળ પ્રધાનમંત્રી જન આરોગ્ય યોજનાને શરૂ કરવા માટેની તૈયારીઓની સમીક્ષા પણ કરી હતી.
Ex Output:
ఆయుష్మాన్ భారత్ లో... | అలాగే చట్టాన్ని గౌరవించి నడచుకునే కార్పొరేట్ సంస్థల సులభతర వ్యాపారానికి మరింత వీలు కల్పించే ఏర్పాటూ ఇందులో ఉంది.
| 1 | NIv2 | task1013_pib_translation_gujarati_telugu | fs_opt | [
-0.11790769547224045,
0.28203633427619934,
-0.35900959372520447,
-0.2255256325006485,
0.2053835242986679,
-0.21661309897899628,
-0.2287624627351761,
0.4272487163543701,
-0.21831880509853363,
0.44538432359695435,
-0.38977527618408203,
0.03396124392747879,
-0.3820083737373352,
0.221273154020... |
Teacher: 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.
Teacher: Now, understand the problem? If you are still confused, see the following exa... | the addams family | 2 | NIv2 | task306_jeopardy_answer_generation_double | fs_opt | [
-0.3575451076030731,
0.5617018342018127,
-0.12767113745212555,
-0.20503801107406616,
-0.2818334698677063,
0.4709457457065582,
-0.25681960582733154,
-0.10176665335893631,
0.011956729926168919,
-0.025378039106726646,
0.31671273708343506,
0.14031895995140076,
-0.4943021535873413,
-0.818830072... |
Instructions: Given a disfluent sentence, modify the sentence to it to its equivalent fluent form, preserving the meaning of the sentence.
Input: What do some researchers believe is the earliest-diverging animal phylum or wait tell me what all other animal phyla lack?
Output: | What do all other animal phyla lack? | 3 | NIv2 | task1195_disflqa_disfluent_to_fluent_conversion | zs_opt | [
-0.7464569807052612,
0.44487106800079346,
-0.593407392501831,
-0.38038933277130127,
-0.7739229202270508,
-0.742567777633667,
-0.30253905057907104,
0.6230091452598572,
0.24916967749595642,
-0.4866092801094055,
-0.21391227841377258,
-0.7039262056350708,
-1.1354506015777588,
0.367199242115020... |
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 anything rude or disrespectful about someone's identity, including appearance, race, gender, and sexual orientation.
Example ... | Non-identity-attack
| 3 | NIv2 | task325_jigsaw_classification_identity_attack | fs_opt | [
-0.24400678277015686,
0.3844689726829529,
0.26081615686416626,
0.3304210305213928,
0.0032196971587836742,
-0.11089232563972473,
0.8635126352310181,
0.6475659012794495,
0.5893607139587402,
0.3056040406227112,
0.057920776307582855,
-0.278889924287796,
-0.3126032054424286,
-0.7140392065048218... |
Given a 'poster' sentence and a corresponding 'response' (often, from Facebook or Reddit)classify the sentiment of the given response into four categories: 1) Positive, 2) Negative, 3) Neutral, and 4) Mixed if it contains both positive and negative.
One example is below.
Q: Poster: Stopped by Fashion Week and got to ha... | Mixed | 9 | NIv2 | task823_peixian-rtgender_sentiment_analysis | fs_opt | [
-0.6188086271286011,
-0.3132026791572571,
0.577176570892334,
0.28199630975723267,
0.743741512298584,
-0.41471898555755615,
0.07487943768501282,
0.13995830714702606,
0.33445286750793457,
0.5164376497268677,
0.07015372812747955,
0.314450204372406,
0.02052340842783451,
-0.13647447526454926,
... |
Definition: You are given a statement written in Marathi. 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: अष्टविनायक म्हणजे <MASK>ातील आठ मानाची व प्रतिष्ठेची गणपतीची देवळे आहेत. पश्चिम महार... | महाराष्ट्र | 2 | NIv2 | task950_wiki_cloze_mr_multiple_choice_question_answering | zs_opt | [
0.3778282701969147,
0.3125837445259094,
-0.3810230791568756,
-0.3505725562572479,
-0.668936014175415,
-0.8848085403442383,
0.9388540983200073,
0.37887436151504517,
-0.28884029388427734,
-0.08951465040445328,
-0.35226061940193176,
-0.1175827756524086,
-0.11090750992298126,
0.048999190330505... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given an input list A. You need to extract and sort the unique digits used in the list in ascending order. Return -1 if there is no digit in the list.
['q', 'c', '325', 'z', '3', 'a', 'z', 'd']
Output: | 2, 3, 5 | 1 | NIv2 | task637_extract_and_sort_unique_digits_in_a_list | zs_opt | [
-0.19637879729270935,
0.33348190784454346,
-0.4635644555091858,
-0.6352148056030273,
0.1318325251340866,
0.6334395408630371,
0.8560472726821899,
-0.3259674906730652,
-0.7703465223312378,
0.44755038619041443,
-0.2563302516937256,
-0.2600202262401581,
-0.7718789577484131,
-0.5571540594100952... |
Definition: In this task, you need to count the number of nouns/verbs in the given sentence.
Input: Sentence: 'A plant grows in a gold and black vase in the corner'. Count the number of verbs in this sentence.
Output: | 1 | 2 | NIv2 | task155_count_nouns_verbs | zs_opt | [
0.4463667869567871,
0.9906013011932373,
-0.48840269446372986,
-0.20359069108963013,
-0.5729879140853882,
0.30338820815086365,
0.305942565202713,
0.43210315704345703,
-0.2131698727607727,
-0.1426234394311905,
-1.004915714263916,
-0.29847732186317444,
-0.6972376704216003,
0.7662569880485535,... |
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 ... | 3606yw1952R5689096168499845228Q72193037 | 9 | NIv2 | task267_concatenate_and_reverse_all_elements_from_index_i_to_j | fs_opt | [
-0.13312111794948578,
0.1320875585079193,
-0.26153379678726196,
-0.4074106812477112,
-0.24966391921043396,
-0.2409892976284027,
0.38481640815734863,
0.20846647024154663,
-0.624791145324707,
0.12050583213567734,
-1.0423753261566162,
-0.07650640606880188,
0.026574432849884033,
-0.54025441408... |
Given a comment, classify it into a 'hate' speech or 'not hate' speech. Answer using 'hate' or 'not hate'.
One example is below.
Q: I hate women. All of them are useless.
A: hate
Rationale: Gender discrimination is shown in this comment. Hence, it is classified as hate speech.
Q: WHAT THE FUCK IS THIS ??!????! Disgusti... | not hate | 9 | NIv2 | task1604_ethos_text_classification | fs_opt | [
-0.4155874252319336,
1.1518049240112305,
0.2178233116865158,
0.5570100545883179,
-0.39312273263931274,
-1.1842947006225586,
0.6731711626052856,
0.9875048398971558,
0.9508265852928162,
0.5148451328277588,
-0.3395478129386902,
-0.14570578932762146,
-0.49681904911994934,
-0.3493172526359558,
... |
You will be given a definition of a task first, then some input of the task.
Based on the given context, craft a common-sense question, especially those that are LONG, INTERESTING, and COMPLEX. The goal is to write questions that are easy for humans and hard for AI machines! To create such questions, here are some sugg... | Where was the basket purchased ? | 1 | NIv2 | task023_cosmosqa_question_generation | zs_opt | [
0.8414931297302246,
-0.1362852156162262,
-0.46582579612731934,
0.6697623133659363,
0.40428605675697327,
-0.6707842350006104,
0.6283761262893677,
1.0305986404418945,
-0.5389769673347473,
0.32197001576423645,
-0.6248642206192017,
0.3796359896659851,
-0.33329081535339355,
0.2715156078338623,
... |
In this task, you are given a sentence in Arabic, and your task is to translate it into English.
لقد قُتل ذلك الرجُل وهو بجانبنا | That guy was killed right in front of us inches away. | 0 | NIv2 | task650_opus100_ar_en_translation | zs_opt | [
0.4375540614128113,
0.9753278493881226,
-0.06647419184446335,
-1.2795017957687378,
-0.34156715869903564,
-0.7970521450042725,
0.5792925357818604,
0.00556528102606535,
0.6890478134155273,
0.29300734400749207,
-0.8483356237411499,
0.17697395384311676,
-0.39689338207244873,
0.4583592414855957... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.