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 |
|---|---|---|---|---|---|---|
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that neither agree with nor contradict each other. Your job is to alter sentence 2 so that the pair clearly contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronoun... | People ride bikes outside. | 0 | NIv2 | task189_snli_neutral_to_contradiction_text_modification | zs_opt | [
-0.9588916897773743,
0.5254787802696228,
-0.04287026822566986,
-0.31036338210105896,
-0.11197229474782944,
0.24697312712669373,
-0.16152313351631165,
0.6101272106170654,
0.12825153768062592,
-0.9006202816963196,
-1.4851231575012207,
-0.4860146641731262,
-0.1437828093767166,
-0.017643887549... |
Part 1. Definition
You will be asked how to do a certain task. You should describe a physical process that does not lead to the asked outcome, yet it is closely related to it (i.e., it should use the words that are provided in the input). The physical process can be moving something, arranging something in a certain wa... | Fill a saucepan with water. Place whole ginger root into the saucepan. Turn on the stove to medium-high heat. Cover the saucepan. | 7 | NIv2 | task081_piqa_wrong_answer_generation | fs_opt | [
0.3522048890590668,
0.4748685657978058,
-0.9082462787628174,
0.3483407497406006,
0.36188873648643494,
-0.6612688302993774,
0.19765494763851166,
0.6123448610305786,
-0.20760774612426758,
0.2613018751144409,
0.2996456027030945,
0.05288233608007431,
-0.5864443182945251,
-0.1519833356142044,
... |
You are provided with an "Event", "Intent" and "XEmotion" (PersonX's reactions for the given "Event"). Indicate PersonY's reaction (person feels) at the end of this event. Provide one reaction for PersonY. If there's nothing that can be implied, respond as None
Q: Event:PersonX gets the ice cream. Intent: 1) to play cu... | happy for ice cream | 4 | NIv2 | task924_event2mind_word_generation | zs_opt | [
0.27402251958847046,
0.19689805805683136,
0.010327144525945187,
-0.35917162895202637,
-0.7200689911842346,
-0.5360236167907715,
0.9417422413825989,
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-0.5157040357589722,
0.7202973365783691,
-0.22502978146076202,
-0.7016441822052002,
0.07927635312080... |
In this task you are given a medical question pair hand-generated. Your task is to classify a given post into two categories 1) 'Similar' if the given two questions have a same connotation 2) 'Dissimilar' if the given two questions have a different connotation or meaning.
[EX Q]: Sentence1: Can ibs calm down at night ... | Dissimilar
| 6 | NIv2 | task1645_medical_question_pair_dataset_text_classification | fs_opt | [
0.08609955757856369,
0.3639996647834778,
-0.657882571220398,
0.160186305642128,
-0.4127398133277893,
-0.02005438134074211,
0.14421582221984863,
0.7435572147369385,
-0.015481640584766865,
-0.11876615136861801,
-0.8293848037719727,
0.740462601184845,
-0.7318966388702393,
-0.20780867338180542... |
Given a sentence with a missing word, pick the answer option that best fills out the missing word in the sentence. Indicate each answer with its index ('a', 'b', 'c', 'd').
One example: Female snakes incubate eggs inside of their bodies, giving birth to live young of ____ or more. \Question: Choose the right answer fro... | b | 6 | NIv2 | task1360_numer_sense_multiple_choice_qa_generation | fs_opt | [
-1.038359522819519,
0.39356303215026855,
-0.6428253650665283,
-0.2664572596549988,
-0.5485038161277771,
0.1207275539636612,
0.386466383934021,
0.8902199864387512,
-0.032711662352085114,
-0.08344951272010803,
-0.029802031815052032,
0.4766021966934204,
-1.1246256828308105,
0.2956363558769226... |
You are given a sentence in Persian. Your job is to translate the Farsi sentence into Hebrew.
Ex Input:
پس چرا واقعا می خواین بدونید که اونی که توی فیس بوکه ، کیه ؟ مگر این که قصد سوء استفاده یا آزار رسوندن به اونها را به نحوی داشته باشید ؟
Ex Output:
למה שתרצה לדעת מי באמת האדם הזה בפייסבוק, אלא אם כן אתה רוצה לפג... | (צחוק) ואני יודעת מה כמה מכם חושבים, ואתם צודקים בעיקר.
| 1 | NIv2 | task1269_ted_translation_fa_he | fs_opt | [
-0.5313748121261597,
0.12844949960708618,
-0.6018532514572144,
-0.06596126407384872,
-1.1336101293563843,
0.10683101415634155,
0.7858964204788208,
-0.0562555268406868,
1.0830090045928955,
0.005060162860900164,
-0.7635515928268433,
0.5407426357269287,
-0.9137759804725647,
-0.034552857279777... |
Given the task definition, example input & output, solve the new input case.
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... | 21 | 1 | NIv2 | task218_rocstories_swap_order_answer_generation | fs_opt | [
-0.20364737510681152,
0.13748759031295776,
-0.2574089765548706,
0.30348947644233704,
0.2362077385187149,
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0.07679052650928497,
0.7799261212348938,
0.049072615802288055,
0.21324434876441956,
-0.5878601670265198,
-0.07310019433498383,
-0.5534217953681946,
0.04655524343252... |
Detailed Instructions: You are given a statement written in Hindi. 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 .
See one example below:
Problem: Statement: सिग्नेचर केल्विन क्लेन अंडरवियर बुटीक, ब्यूनस आयर्... | २००७ | 4 | NIv2 | task947_wiki_cloze_hi_multiple_choice_question_answering | fs_opt | [
0.389970064163208,
0.8519842028617859,
-0.5175533294677734,
-0.19141796231269836,
-0.08420370519161224,
-0.6394666433334351,
-0.34244680404663086,
0.837499737739563,
-0.16203546524047852,
-0.16372880339622498,
-0.09937518835067749,
0.036779116839170456,
-0.601249635219574,
-0.3174707591533... |
instruction:
Given a sentence in German, generate a new German 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 probabil... | Kleine Mädchen müssen erklären, um Telefonate zu machen.
| 9 | NIv2 | task416_mickey_de_sentence_perturbation_generation | fs_opt | [
-0.17255458235740662,
0.6378951668739319,
-0.13297590613365173,
-0.4262865483760834,
-0.5969706773757935,
-0.32937610149383545,
0.7771030068397522,
0.5948387980461121,
0.11306554079055786,
-0.11660397052764893,
-0.6307876110076904,
0.5897892117500305,
-1.2976551055908203,
-0.47599768638610... |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., Person... | Yes | 1 | NIv2 | task1198_atomic_classification_owant | fs_opt | [
0.20093318819999695,
-0.06986665725708008,
0.3285612463951111,
0.20016640424728394,
0.018086299300193787,
-0.6918623447418213,
0.8998051881790161,
0.4777142405509949,
-0.8215959072113037,
-0.04905543103814125,
-0.15003590285778046,
-0.4021030366420746,
-0.6198176145553589,
-0.0811274349689... |
Given a document, generate a short title of the document. The title should convey the main idea/event/topic about which the document is being written. Note that URLs in the text have been replaced with [Link].
Let me give you an example: In a letter posted on the White House web site Tuesday John Brennan assistant t... | Jeff Sessions to face tough Russia questions at House hearing | 8 | NIv2 | task418_persent_title_generation | fs_opt | [
0.27778294682502747,
-0.03886156529188156,
-0.7072221040725708,
-0.09965884685516357,
0.7208070755004883,
0.06593634933233261,
0.5651264190673828,
0.412537157535553,
-0.29515090584754944,
0.6944752931594849,
0.2814067006111145,
0.9935063123703003,
-0.720798134803772,
-0.055980879813432693,... |
In this task, you're given an ambiguous question (which can be answered in more than one way). Your task is to provide one question which clarifies the input question and it has one unique answer, and also provide an answer to the generated question. Generated question and answer should be separated with a new line.
Ex... | Solution: Who won so you think you can dance: The Next Generation 2016?
Leon "Kida" Burns | 5 | NIv2 | task671_ambigqa_text_generation | fs_opt | [
-0.5450834035873413,
0.2999914288520813,
0.15039928257465363,
-0.6795350909233093,
0.11386638134717941,
0.15343117713928223,
0.45167970657348633,
0.25185367465019226,
-0.4723973572254181,
-0.49517035484313965,
-0.17512813210487366,
0.7029213905334473,
-0.9169617891311646,
0.125190854072570... |
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/existing words removed. Yo... | A bear saw Anna in the distance. | 3 | NIv2 | task068_abductivenli_incorrect_answer_generation | fs_opt | [
0.31492099165916443,
0.12339752167463303,
-0.8768520355224609,
0.30346351861953735,
-0.2175305187702179,
-0.2564049959182739,
0.5272348523139954,
0.3890129327774048,
-0.7771809101104736,
-0.7377997636795044,
-0.3705786466598511,
0.6387666463851929,
-0.892232358455658,
-0.41352546215057373,... |
Given the task definition and input, reply with output. Given a pair of words, deduce the type of relationship between them. The various types of relations are: 'HYPER', 'COORD' and 'RANDOM'. Let's denote the first word by X and the second word by Y. A COORD relationship holds when X and Y belong to the same semantic c... | RANDOM | 5 | NIv2 | task1505_root09_semantic_relation_classification | zs_opt | [
-0.9563644528388977,
0.4801640808582306,
0.41098254919052124,
-0.31507939100265503,
-0.7057867050170898,
0.4189416170120239,
0.6238389015197754,
-0.07750344276428223,
0.4547315239906311,
-1.0408883094787598,
-1.2950208187103271,
-0.10611314326524734,
-0.3210417628288269,
0.2831475436687469... |
Instructions: In this task you're given a question and you have to paraphrase the question to create the output question while retaining the meaning of the original question.
Input: What is the difference between FDI and FII?
Output: | How does the FDI and FII help in the Indian economy? | 3 | NIv2 | task1345_glue_qqp_question_paraprashing | zs_opt | [
-0.37799519300460815,
0.3498366177082062,
-0.19418390095233917,
0.03533966466784477,
-0.6723015308380127,
-0.21551254391670227,
0.519375741481781,
0.8360029458999634,
0.5681964755058289,
-0.14790552854537964,
-1.962145447731018,
0.034507036209106445,
-0.5470004677772522,
0.4128112196922302... |
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into English.
Input: Consider Input: 二つの側面から物事を進めなさいということなのです。
Output: It's to say we operate on two levels.
Input: Consider Input: テクノロジーは皆が共有できる社会的な方法を作ることを可能にしています
Output: Technology is just generally being used to allow us to ... | Output: Something interesting came out of "" The Abyss, "" which was that to solve a specific narrative problem on that film, which was to create this kind of liquid water creature, we actually embraced computer generated animation, CG.
| 2 | NIv2 | task1222_ted_translation_ja_en | fs_opt | [
-0.11046366393566132,
-0.06401996314525604,
-0.08992043137550354,
0.44574275612831116,
0.2034701406955719,
-0.8641151189804077,
-0.3368381857872009,
0.15538519620895386,
0.012059452012181282,
0.40150827169418335,
-0.4409739375114441,
0.4168074131011963,
0.09155118465423584,
-0.313866019248... |
Given the task definition, example input & output, solve the new input case.
Given a sentence in the Filipino, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Example: Natalo ng Italya ang Portugal sa puntos na 31-5 sa Grupong C... | 今まで天文学者の間では輪はほぼ完全に扁平で、厚みの差は数メートルほどしかないと考えられてきた。 | 1 | NIv2 | task1119_alt_fil_ja_translation | fs_opt | [
-0.07131604850292206,
0.7432888746261597,
-0.6424744725227356,
0.36917775869369507,
0.13544118404388428,
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0.3894653618335724,
0.6864392757415771,
0.261785626411438,
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-0.7259571552276611,
0.5503482222557068,
-0.16449224948883057,
0.5012403130531311,
... |
Q: 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 det... | Yes | 7 | NIv2 | task1205_atomic_classification_isafter | zs_opt | [
0.5023480653762817,
0.39984339475631714,
0.16911464929580688,
0.06699466705322266,
-0.4709694981575012,
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1.2185832262039185,
0.4889243543148041,
-0.6544378399848938,
-0.36454761028289795,
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-0.6232227087020874,
0.4310792684555053... |
Definition: You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Portugese.
Input: Y éste es más o menos, un pan de harina integral, artesanal, de una pequeña panadería.
Output: | E este é mais ou menos, um pão integral, feito à mão, numa padaria pequena. | 2 | NIv2 | task1104_ted_translation_es_pt | zs_opt | [
0.1371428221464157,
1.103014588356018,
-0.004703901708126068,
0.2821395993232727,
-0.15348675847053528,
-0.492134690284729,
-0.6165655851364136,
1.9894828796386719,
0.3403341472148895,
-0.08819941431283951,
-1.142045021057129,
0.27400755882263184,
-0.3294565677642822,
0.31617069244384766,
... |
Detailed Instructions: In this task, you are given a abstract of article and corresponding title of an article. Your task is to generate label "yes" if title is right for article, otherwise generate "no".
See one example below:
Problem: Abstract: This study was designed to determine the influence of a long-term, modera... | yes | 4 | NIv2 | task1587_scifact_classification | fs_opt | [
0.017892727628350258,
0.4379643499851227,
-0.7648996114730835,
0.5148573517799377,
0.5026144981384277,
-0.3166167438030243,
0.34362292289733887,
0.675819993019104,
-0.009649790823459625,
-0.09333230555057526,
-0.7158676385879517,
0.28691452741622925,
-0.814211368560791,
0.3429555296897888,... |
Definition: In this task, you will be presented with the directions of a recipe separated by "," and have to fill in the "___" which is a step that is missing from the recipe.
Input: ______,Add eggs, milk, vanilla, margarine and pecans.,Beat well and pour into a 9-inch deep dish pie shell.,Bake in a 350° oven for 40 to... | Combine sugar, cocoa, flour, cornmeal and dash of salt in a mixing bowl. | 2 | NIv2 | task572_recipe_nlg_text_generation | zs_opt | [
-0.1979602873325348,
0.3112336993217468,
0.06766676902770996,
0.14820532500743866,
-0.2911960482597351,
1.1476364135742188,
0.1715587079524994,
0.5047973394393921,
-0.287845253944397,
-0.10409943759441376,
-0.16467341780662537,
0.23623806238174438,
-0.10461551696062088,
-0.1435967087745666... |
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... | Against | 3 | NIv2 | task1646_dataset_card_for_catalonia_independence_corpus_text_classification | fs_opt | [
-0.17306090891361237,
0.9219399690628052,
-0.07621415704488754,
0.13255397975444794,
-0.41243308782577515,
-1.1485192775726318,
0.24476754665374756,
0.7527003288269043,
-0.21320348978042603,
0.572828471660614,
-0.31047487258911133,
-0.027382874861359596,
0.28792181611061096,
-0.27338302135... |
Instructions: A ploynomial equation is a sum of terms. Here each term is either a constant number, or consists of the variable x raised to a certain power and multiplied by a number. These numbers are called weights. For example, in the polynomial: 2x^2+3x+4, the weights are: 2,3,4. You can present a polynomial with th... | 311 | 3 | NIv2 | task090_equation_learner_algebra | zs_opt | [
0.35813426971435547,
1.0579708814620972,
-0.7302253246307373,
-0.7171148061752319,
-0.44157272577285767,
-0.41698312759399414,
1.053587794303894,
0.6857430934906006,
-0.028023220598697662,
-0.9035772681236267,
-0.5463487505912781,
0.9308722019195557,
-0.8092875480651855,
0.0937415435910224... |
You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Portugese.
Q: لذا فإن أول ما فعلناه هو أننا أحضرنا حقيبة من قطع الحلوى وتمشينا حول حرم الجامعة وتحدثنا مع الطلاب والعمداء والموظفين وطلبنا منهم معلومات عن كلمات المرور الخاصة بهم
A: | Então a primeira coisa que fizemos foi, comprámos um saco de guloseimas e andámos pelo "" campus "" e falámos com estudantes, professores e funcionários, e pedimos-lhes informações sobre as suas palavras-passe. | 4 | NIv2 | task1109_ted_translation_ar_pt | zs_opt | [
-0.15975289046764374,
0.7409175634384155,
0.09439949691295624,
-0.7703765630722046,
-0.6905933618545532,
-0.2407420575618744,
-0.7415414452552795,
0.5056079030036926,
0.6004226207733154,
0.2861488461494446,
0.07910873740911484,
-0.4494835138320923,
-0.6791709661483765,
0.019265230745077133... |
In this task you will be given a string and you should find the longest substring that is a palindrome. A palindrome is a string that is the same backwards as it is forwards. If the shortest possible palindrome is length 1 you should return the first character.
One example is below.
Q: gocogccocco
A: gocog
Rationale: T... | tttiittt | 9 | NIv2 | task850_synthetic_longest_palindrome | fs_opt | [
-0.3752232789993286,
0.8539413213729858,
0.10143153369426727,
-0.16874033212661743,
-0.25952431559562683,
-0.5354849696159363,
1.060642957687378,
-0.3424112796783447,
-0.17312142252922058,
-0.35307565331459045,
-0.7529905438423157,
0.0916648805141449,
-0.5085161924362183,
0.356837302446365... |
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Let me give you an example: concept: Selena Gomez question: what city was selena gomez born in?
The answer to this example can be: New York City
Here is why... | ['Canada', 'Australia', 'South Africa', 'Zambia', 'United Kingdom', 'Zimbabwe', 'Uganda', 'New Zealand', 'Turks and Caicos Islands', 'Tanzania'] | 8 | NIv2 | task1601_webquestions_answer_generation | fs_opt | [
0.024123787879943848,
0.7990038394927979,
0.37681642174720764,
0.1421452760696411,
-0.16545715928077698,
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0.2459222674369812,
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0.1838259994983673,
0.007704068906605244,
-0.20717130601406097,
1.1603169441223145,
-1.0735846757888794,
-0.15157501399517... |
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'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 inconsist... | His infection was much better than he thought. | 0 | NIv2 | task068_abductivenli_incorrect_answer_generation | fs_opt | [
0.5131063461303711,
0.1602603942155838,
-0.3140408992767334,
0.4746479094028473,
0.24160128831863403,
-0.4387953281402588,
0.29004886746406555,
0.6717642545700073,
-0.4744865894317627,
-0.27507901191711426,
-0.3766981363296509,
0.40909120440483093,
-0.2562475800514221,
-0.2600021958351135,... |
In this task, you will use your knowledge about language (and common sense) to determine what element the marked number refers to. The numbers are marked with two underlines around them, like: _ number _. There are several possible answers, you'll need to choose the proper one. Carefully read the given text, pay specia... | OTHER
| 6 | NIv2 | task304_numeric_fused_head_resolution | fs_opt | [
0.036846693605184555,
0.6596204042434692,
-0.589952826499939,
0.7683455944061279,
-0.21541038155555725,
-0.23453554511070251,
1.4901676177978516,
0.8462929725646973,
0.047274209558963776,
0.05678077042102814,
-0.08541561663150787,
0.356220006942749,
-0.36924809217453003,
-0.258493453264236... |
The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Catalan Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence in the Catalan language. 2)... | -Mi amor, contradices a todo el mundo -dijo su esposa, con su risa habitual-.
| 0 | NIv2 | task1652_opus_books_ca-en_translation | fs_opt | [
0.3600175976753235,
1.1206166744232178,
-0.4207325577735901,
-0.4017559885978699,
-0.21822589635849,
-0.9773442149162292,
0.7615309953689575,
0.021919898688793182,
0.16466759145259857,
-0.278656542301178,
0.2116282880306244,
0.586997926235199,
-0.8355387449264526,
0.14596715569496155,
0.... |
You will be given a definition of a task first, then some input of the task.
Given a sentence in Italian, generate a new Italian 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 ... | È probabile che troverete un ing intorno a un lago. | 1 | NIv2 | task408_mickey_it_sentence_perturbation_generation | zs_opt | [
-0.35965168476104736,
0.5894390344619751,
-0.46019530296325684,
0.1764756143093109,
-0.20910564064979553,
-0.49654126167297363,
0.2727949619293213,
1.107353925704956,
-0.05796695500612259,
-0.620516836643219,
-0.7397535443305969,
-0.06267066299915314,
0.16385531425476074,
0.248787611722946... |
Q: In this task you will be given a list of integers. For every element in the list, if the element is even you should divide by 4, if the element is odd you should multiply by 4 then add 2. The output should be a list of numbers that is the result of applying that logic to the input list. You should not round any deci... | [-9.0, -24.5, 5.5, -5.0, 18.5, 2.0, 94, -14.5, -16.5] | 7 | NIv2 | task368_synthetic_even_or_odd_calculation | zs_opt | [
-0.656699538230896,
0.501066267490387,
-0.16534098982810974,
-0.17057017982006073,
-0.02885507047176361,
0.13218483328819275,
1.270218849182129,
0.07160158455371857,
-0.5884376764297485,
0.3725539445877075,
-0.45890194177627563,
-0.538200318813324,
-0.5358778238296509,
-0.4623940587043762,... |
Detailed Instructions: Given a premise, an initial context, an original ending, and a new ending, the task is to generate the counterfactual context that is aligned with the new ending. Each instance consists of a five-sentence story. The premise is the first sentence of a story, and the second sentence, which is the i... | I asked my teacher about it. | 9 | NIv2 | task270_csrg_counterfactual_context_generation | zs_opt | [
0.33144181966781616,
0.31294679641723633,
-0.751154363155365,
0.4095615744590759,
0.28828686475753784,
-1.2387909889221191,
0.1296011209487915,
1.5697064399719238,
0.007844533771276474,
0.3094710111618042,
-0.17509102821350098,
-0.42514899373054504,
-0.34628117084503174,
0.1164036095142364... |
Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period symbol is used f... | NUM | 9 | NIv2 | task1167_penn_treebank_coarse_pos_tagging | fs_opt | [
0.28374457359313965,
0.1589474081993103,
-0.05219009891152382,
0.07523404061794281,
-0.0786411464214325,
-0.3901224136352539,
0.5379354357719421,
0.5887260437011719,
-0.4058544933795929,
-0.10098035633563995,
-0.5820791721343994,
0.05992775782942772,
-0.38873010873794556,
0.415646076202392... |
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
In a medium bowl, mix ground nuts and bread crumbs. Stir in olive oil, tomato pa... | ground toasted mixed nuts, bread crumbs, extra virgin olive oil, tomato paste, hot sauce, green onion, flat leaf parsley | 5 | NIv2 | task571_recipe_nlg_ner_generation | zs_opt | [
0.10348829627037048,
0.8010212779045105,
0.22425684332847595,
0.5234992504119873,
-0.32560276985168457,
0.008054465055465698,
0.8990617990493774,
0.10592874139547348,
-0.3458464741706848,
-0.4018975496292114,
-0.27017664909362793,
-0.40975654125213623,
-0.4978063702583313,
-0.3357790410518... |
Given the task definition, example input & output, solve the new input case.
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
Example: 地球が今よりも無垢だった時代を訪れたかのようでした
Output: كان الأمر كزيارة أكثر عصور البراءة على كوكب الأرض
The Japanese sentence is correctly translated into A... | بالنسبة لي ، هذه هي السعادة الحقيقية. | 1 | NIv2 | task1224_ted_translation_ja_ar | fs_opt | [
-0.3549543023109436,
0.42563939094543457,
0.045888688415288925,
-0.21808478236198425,
-0.30439871549606323,
0.0156690776348114,
0.738786518573761,
-0.20336584746837616,
0.1762336939573288,
0.06368504464626312,
-0.6882316470146179,
0.32873862981796265,
-0.27176013588905334,
0.03672527521848... |
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'.
Example input: Problem: on a sum of money , the simple interest for 2 years is rs . 330 , while the compound interest is rs . 340 , ... | b | 3 | NIv2 | task1419_mathqa_gain | fs_opt | [
0.690272331237793,
-0.007585801649838686,
-0.4213407039642334,
-0.1887206733226776,
-0.3622415065765381,
-0.4974510073661804,
1.455304741859436,
1.0482382774353027,
-0.008522843942046165,
0.049272533506155014,
-0.69792240858078,
0.1565963625907898,
-0.5936322808265686,
-0.3073239028453827,... |
Given the task definition and input, reply with output. In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to classify the command into one of these seven categories: (1) majority, (2) unique, (3) superlative, (4) count, (5) comparative, (6) a... | comparative | 5 | NIv2 | task212_logic2text_classification | zs_opt | [
0.03586389496922493,
-0.3576558232307434,
-0.16908003389835358,
0.4263623356819153,
0.49386852979660034,
-0.5277717709541321,
0.6848620772361755,
0.49370306730270386,
0.3539170026779175,
-0.10391248017549515,
-0.19262877106666565,
0.20231680572032928,
0.09477421641349792,
0.523538112640380... |
In this task you will be given a string of characters. You should remove all vowels from the given string. Vowels are: i,e,a,u,o. The character 'y' or 'Y' does not count as a vowel.
Let me give you an example: hNarAik
The answer to this example can be: hNrk
Here is why: The three vowels in the input 'a, 'A', and 'i' a... | tnjWQqDjm | 8 | NIv2 | task365_synthetic_remove_vowels | fs_opt | [
0.4512941241264343,
1.0454833507537842,
-0.26069772243499756,
-0.7819546461105347,
0.28745847940444946,
-0.6253830194473267,
0.3958795666694641,
-0.017008282244205475,
0.06871575117111206,
-0.3505731225013733,
-0.49314379692077637,
-0.22080755233764648,
-0.186612069606781,
-0.8438570499420... |
In this task, you are given a sentence in the Hindi language and a corresponding English translation of the Hindi sentence. Your task is to generate a label "Yes" if the translation is correct, otherwise generate label "No". In the translation, English sentence should preserve the number as it is and it should be in se... | Yes | 6 | NIv2 | task426_hindienglish_corpora_hi-en_classification | fs_opt | [
0.07133245468139648,
0.05034187436103821,
0.561732292175293,
0.11873873323202133,
0.3273972272872925,
-0.5044373869895935,
-0.7262011766433716,
0.4429767429828644,
-0.15868553519248962,
-0.2796000838279724,
-0.2637624144554138,
-0.03890315815806389,
-0.098765529692173,
0.4308314323425293,
... |
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to classify the conversation either convey 'No emotion' or 'Happiness' by providing '1' and '0', respectively.
Ex Input:
Person1: I hear that Tom got divorced , and I don ’ t k... | 0
| 1 | NIv2 | task1536_daily_dialog_happiness_classification | fs_opt | [
0.39476478099823,
0.3525843620300293,
-0.05302390456199646,
0.4160672128200531,
0.18825484812259674,
-0.1501811295747757,
0.3752553462982178,
0.4625743329524994,
0.26828286051750183,
0.2402370274066925,
0.1225246787071228,
-0.2503182590007782,
-0.3699076175689697,
0.22692802548408508,
0.... |
Part 1. Definition
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.
Part 2. Example
[0,1,0,2,5,1]
Answer: [2,5]
Explanation: ... | [7, 4, 6] | 7 | NIv2 | task097_conala_remove_duplicates | fs_opt | [
-0.09937126934528351,
0.21734358370304108,
-0.24126668274402618,
-0.34095990657806396,
0.34859177470207214,
-0.1749008148908615,
1.2873269319534302,
0.27304133772850037,
-0.5242633819580078,
0.3114033341407776,
-1.1439841985702515,
-0.33737578988075256,
-0.3624131381511688,
-0.500360429286... |
Detailed Instructions: In this task, you will be given a short story. One sentence from the story is chosen. Consider the events that happen after that sentence. Is any of them directly caused by it, or is made possible by it? You should write your answer in the form " A >causes/enables> B". Try to use phrases and sent... | I agree to play chess with him >Causes/Enables> My brother beats me at chess | 9 | NIv2 | task748_glucose_reverse_cause_event_detection | zs_opt | [
0.09456463158130646,
0.8088194727897644,
-0.2827315628528595,
-0.4678260087966919,
-0.23373743891716003,
-1.0708388090133667,
0.6462363600730896,
0.437591016292572,
0.30738359689712524,
-0.7194837331771851,
-0.17670220136642456,
0.2269984483718872,
-0.406814843416214,
0.12416551262140274,
... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
You are given a background paragraph that describes one or more causal or qualitative relationships such as a relationship in economics or a scientific law and a story that makes use of the concepts ... | Dale's. | 0 | NIv2 | task061_ropes_answer_generation | fs_opt | [
0.1067013069987297,
0.22933818399906158,
-0.03094182163476944,
0.021784719079732895,
0.2283613085746765,
-0.39066004753112793,
0.09659194201231003,
1.3561184406280518,
-0.6401567459106445,
0.45250770449638367,
-0.8295964002609253,
-0.0046731955371797085,
-1.187820553779602,
0.0324365198612... |
Given an entity as input, output another entity which is part of the input entity. These are entities of meronym. In linguistics, meronymy is a semantic relation between a meronym denoting a part and a holonym denoting a whole. In simpler terms, a meronym (i.e., output entity) is in a part-of relationship with its holo... | blood vessel
| 6 | NIv2 | task471_haspart_answer_generation | fs_opt | [
-1.1951613426208496,
0.4158652424812317,
0.6270331740379333,
-0.6847484111785889,
-0.4020204544067383,
-0.450836181640625,
-0.6597363948822021,
0.31458771228790283,
0.026632118970155716,
-1.0041615962982178,
-0.44009196758270264,
-0.45388472080230713,
-0.17865248024463654,
0.15381850302219... |
Q: 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".
Paragraph: At the height of the SARS 1 crisis in spr... | False | 7 | NIv2 | task1162_coda19_title_classification | zs_opt | [
0.24997606873512268,
0.5949636697769165,
-0.5069534778594971,
-0.5331586599349976,
0.25839924812316895,
-0.1960206925868988,
0.36636269092559814,
0.5806161165237427,
-0.3834725320339203,
0.41665351390838623,
-0.9050319194793701,
0.6740730404853821,
-0.29972904920578003,
-0.1455647796392440... |
Teacher:In this task, you're given the beginning and the middle of a three-part story. Your job is to complete the short story by writing a probable ending. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a child. Avoid using any irrelevant extra information when creating t... | Finally, they decided to keep it. | 6 | NIv2 | task071_abductivenli_answer_generation | zs_opt | [
-0.32488930225372314,
0.3792056441307068,
-0.4041554927825928,
-0.657346248626709,
-0.4430873394012451,
-0.19872106611728668,
0.6578025221824646,
0.5242599248886108,
-0.24955952167510986,
-0.8108314275741577,
-0.022028815001249313,
0.3368939757347107,
-0.428713858127594,
-0.358015954494476... |
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
Input: Consider Input: The site collects your demographic information for an unspecified purpose. Collection happens when y... | Output: Not Specified
| 2 | NIv2 | task683_online_privacy_policy_text_purpose_answer_generation | fs_opt | [
-0.45911645889282227,
-0.08405277878046036,
-0.8772801160812378,
0.24334609508514404,
-0.6293225288391113,
-0.834784984588623,
-0.07487799972295761,
-0.3616385757923126,
0.20848162472248077,
1.0106110572814941,
0.23923613131046295,
0.14583219587802887,
-0.35048454999923706,
-0.936601340770... |
Teacher: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 your answer in the form " A >causes/enables> B". ... | Joe sees his car is snowed in >Causes/Enables> Joe goes outside and gets his snow shovel | 6 | NIv2 | task614_glucose_cause_event_detection | zs_opt | [
-0.3146003186702728,
0.19445490837097168,
-0.30113714933395386,
0.2035408318042755,
0.040261030197143555,
-0.7097954750061035,
0.015301122330129147,
1.4761570692062378,
-0.25746721029281616,
0.2077028602361679,
-0.5800150036811829,
-0.354647159576416,
-0.3908573389053345,
-0.68307304382324... |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Arabic.
Ex Input:
אז בואו ניקח את כל הילדים, נשים אותם בלולים, ונכריח אותם לשחק חודשים. הם כולם יהיו גאונים וילכו להרווארד. "" איך אתה מונע מאנשים לפעול כך בקשר לנתונים שאתה מפתח?
Ex Output:
إذاً دعونا نضع الأطفال في حظائر و نتركهم ... | و قلت ، "" مو ، أنت على حق. إننا... كلا ، ولكننا نفعل ذلك من قبل
| 1 | NIv2 | task1237_ted_translation_he_ar | fs_opt | [
-0.593716025352478,
0.17753691971302032,
-0.7790815830230713,
-0.427960604429245,
-0.9654151201248169,
0.06820894032716751,
0.7732848525047302,
-0.2758154273033142,
0.691481351852417,
-0.690423846244812,
-0.8143361210823059,
0.9618360996246338,
-0.859143853187561,
-0.24371200799942017,
1... |
Q: 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.
15 ounces kidney beans, 15 ounces chickpeas, 34 cup fat-free Italian salad dressing, 5 chopped baby carrots, 12 diced onion, 1 minced garlic clove, 2 dice... | kidney beans, chickpeas, Italian salad dressing, baby carrots, onion, garlic, celery ribs, romaine lettuce leaves, water, tomatoes | 7 | NIv2 | task570_recipe_nlg_ner_generation | zs_opt | [
-0.4175052344799042,
0.4803774654865265,
-0.1665293574333191,
0.6768194437026978,
-0.4870310425758362,
-0.3899012804031372,
0.9207308292388916,
0.8976094722747803,
-0.04895063489675522,
-0.22704720497131348,
0.5778863430023193,
0.4010546803474426,
-0.9058398008346558,
-0.04643160104751587,... |
Part 1. Definition
In this task you will be given a process, and a question. The process contains a sequence of steps that happen in order. The question asks about the effect of a certain event on another event. If the first event has a positive effect on the second event, answer with "for", if it has a negative effect... | for | 7 | NIv2 | task1727_wiqa_what_is_the_effect | fs_opt | [
-0.1299123764038086,
-0.07929518818855286,
-0.7273551225662231,
0.4007117748260498,
0.15961311757564545,
-0.7928184270858765,
0.048192523419857025,
1.578184723854065,
-0.29721376299858093,
0.22741283476352692,
-0.40022844076156616,
0.383739709854126,
-0.7842154502868652,
0.1063352301716804... |
Instructions: Given a sentence in Igbo language, translate the sentence to English language keeping the meaning of the original sentence intact
Input: Igbo sentence: Nzube anyị bụ "Mma Health, Fairer Health.
Output: | Our aim is "Better Health, Fairer Health." | 3 | NIv2 | task449_opus_paracrawl_ig_en_translation | zs_opt | [
0.22675009071826935,
0.6714960932731628,
-0.14102545380592346,
-0.5603177547454834,
-0.49552831053733826,
-0.32681992650032043,
-0.10017424821853638,
0.7148047089576721,
0.15945181250572205,
-0.008133401162922382,
-0.07620861381292343,
-0.6962985992431641,
-0.7918741703033447,
-0.620568275... |
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. Indicate your answer by 'Option 1' if the first option is correct, otherwise 'Optio... | Option 2
| 3 | NIv2 | task065_timetravel_consistent_sentence_classification | fs_opt | [
-0.008681656792759895,
0.4086729884147644,
-0.4256243109703064,
0.0906803160905838,
-0.09346286952495575,
-0.41734981536865234,
0.05337100848555565,
1.2475872039794922,
0.22039192914962769,
-0.21666479110717773,
-0.6629021167755127,
-0.10299748182296753,
-0.23151126503944397,
-0.3241534233... |
You will be given a definition of a task first, then some input of the task.
A text is given in Telugu. Translate it from the Telugu language to the Urdu language. The translation must not omit or add information to the original sentence.
دی ورلڈز موسٹ فیمس ٹائیگر
Output: | ది వరల్డ్ స్ మోస్ట్ ఫేమస్ టైగర్ | 1 | NIv2 | task1038_pib_translation_urdu_telugu | zs_opt | [
-0.4661364257335663,
0.5641176104545593,
-0.5543238520622253,
0.7243032455444336,
-0.3603250980377197,
-0.2474263459444046,
0.14527864754199982,
0.02811942808330059,
0.07493983209133148,
-0.1622665524482727,
-0.6610186696052551,
-0.3357807695865631,
-0.3123294711112976,
0.2389262169599533,... |
In this task, you will be presented with a multiple-choice question in Persian, and you should answer the question based on your knowledge. Classify the answers based on options.
Q: حاصل جمع دو عدد ۵۷ است، اگر عدد بزرگ تر سه واحد از سه برابر عدد کوچکتر کمتر باشد عدد بزرگ تر چقدر است؟ <sep> (A) ۲۰ (B) ۴۲ (C) ۱۵ (D) ۳... | B | 4 | NIv2 | task473_parsinlu_mc_classification | zs_opt | [
0.023819681257009506,
0.885530948638916,
-0.5787396430969238,
-0.8134644031524658,
-0.76636803150177,
0.25070688128471375,
1.311348795890808,
0.5245928168296814,
0.487224280834198,
-0.2359181046485901,
-0.7940034866333008,
0.676596462726593,
-0.24620544910430908,
0.06404468417167664,
-0.... |
Definition: You are given a statement written in Bengali. 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: রায়পুরার চতুর্দিকে <MASK>, রহ্মপুত্র, আড়িয়াল খাঁ ও কাঁকন নদী বয়ে গেছে। নদ-নদী ব... | মেঘনা | 2 | NIv2 | task945_wiki_cloze_bn_multiple_choice_question_answering | zs_opt | [
-0.5980668067932129,
0.6574664115905762,
0.16025064885616302,
-0.29683226346969604,
-1.0512127876281738,
-0.45448747277259827,
0.05539247393608093,
0.5845412015914917,
0.2058933675289154,
-0.5234618782997131,
-0.722728967666626,
0.26040613651275635,
-0.44703468680381775,
-0.117235437035560... |
Detailed Instructions: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection o... | eq { hop { nth_argmin { all_rows ; first store ; 3 } ; country } ; spain } | 9 | NIv2 | task210_logic2text_structured_text_generation | zs_opt | [
0.3603009283542633,
0.09649340063333511,
-0.33696478605270386,
0.21452492475509644,
0.212344229221344,
-0.3035462498664856,
0.686592698097229,
0.6575192809104919,
-0.026434987783432007,
-0.07920581102371216,
-0.34706538915634155,
0.04074893519282341,
-0.16705220937728882,
0.623743891716003... |
Detailed Instructions: Given two entities as input, classify as "yes" if second entity is the part of the first entity. Otherwise classify them as "no". 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 mer... | no | 4 | NIv2 | task472_haspart_classification | fs_opt | [
-0.5315021276473999,
0.30863478779792786,
0.562002420425415,
0.11253928393125534,
-0.17325639724731445,
-1.1421740055084229,
0.08507062494754791,
0.7331956624984741,
0.678385317325592,
-0.5389967560768127,
-0.48830610513687134,
-0.040612369775772095,
-0.3655414879322052,
0.2218751907348632... |
In this task, you are given sentences from movie reviews. The task is to classify a sentence as "POS" if the sentiment of the sentence is positive or as "NEG" if the sentiment of the sentence is negative
Example Input: Like Schindler 's List , The Grey Zone attempts to be grandiloquent , but ends up merely pretentious... | POS
| 3 | NIv2 | task363_sst2_polarity_classification | fs_opt | [
-0.874464750289917,
0.10220390558242798,
0.3487253785133362,
-0.4485514163970947,
0.49556347727775574,
-0.7197391986846924,
0.6270843744277954,
0.5266616940498352,
0.39869624376296997,
0.7060987949371338,
-0.7069884538650513,
-0.7355495095252991,
0.08559500426054001,
-0.3546634316444397,
... |
Definition: In this task, You are given an open-domain question that can be answered based on factual information. Your task is to provide \*short\* answer (in a few words only) for the given question. The short answer can be one or more entities or it can also be boolean \*yes\* or \*no\*.
Input: who was the president... | Dwight D. Eisenhower | 2 | NIv2 | task582_naturalquestion_answer_generation | zs_opt | [
-0.4924485981464386,
0.7223840355873108,
-0.28142043948173523,
0.5018056035041809,
-0.5139228105545044,
-0.07997352629899979,
1.4140057563781738,
0.36871612071990967,
0.426409512758255,
-0.1439969390630722,
-1.3114237785339355,
0.22757506370544434,
-0.04813851788640022,
0.06718799471855164... |
Given the task definition and input, reply with output. In this task, you are given two sentences in the English language (Sentence 1 and Sentence 2). Your task is to identify the connecting word between the two sentences.
Sentence 1:One story ( rejected by Daly ) claims that he won the $50,000 in a poker match . Sent... | however | 5 | NIv2 | task563_discofuse_answer_generation | zs_opt | [
-0.48178017139434814,
0.7986744046211243,
0.43169575929641724,
-0.573698103427887,
-0.10765987634658813,
-0.21494713425636292,
-0.17705276608467102,
-0.029519934207201004,
0.3507448434829712,
-0.019006453454494476,
-0.22832593321800232,
0.3530226945877075,
-0.5570616126060486,
-0.395911097... |
Detailed Instructions: You are given a sentence in Persian. Your job is to translate the Farsi sentence into Spanish.
Q: همه ی این فیلم ها ، همه ی این فیلم های مستند را برای تعداد بسیار کمی تماشاگر ساختم.
A: | Hice todas esas películas, todos esos documentales para un público muy reducido. | 9 | NIv2 | task1267_ted_translation_fa_es | zs_opt | [
-0.8728724122047424,
0.3438117504119873,
-0.1833118498325348,
-0.108376145362854,
-0.6873959302902222,
-0.27280259132385254,
-0.0013454339932650328,
0.5751996040344238,
0.5311782956123352,
-0.4304058253765106,
-0.2772877812385559,
-0.12274150550365448,
0.02925809845328331,
0.35880795121192... |
Instructions: In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal for... | Mike nìyẹn, Mike jáde síta láti Mississippi. | 3 | NIv2 | task1619_menyo20k-mt_en_yo_translation | zs_opt | [
-0.37132346630096436,
0.17011962831020355,
-0.04554068297147751,
0.07906542718410492,
0.3440726697444916,
-0.35027074813842773,
0.26769763231277466,
0.6890166401863098,
0.4557756781578064,
-0.07791577279567719,
-0.33697763085365295,
-0.13669991493225098,
-0.646106481552124,
0.1934756338596... |
Teacher:In this task, you are given a sentence in Persian, and your task is to translate it into English.
Teacher: Now, understand the problem? Solve this instance: عکس توسط پان شی یی در ویبو منتشر شده است.
Student: | Photo uploaded by Pan Shiyi to Weibo. | 6 | NIv2 | task662_global_voices_fa_en_translation | zs_opt | [
-0.7867861986160278,
-0.10712644457817078,
-0.07851363718509674,
0.021014582365751266,
-0.48614251613616943,
0.3650789260864258,
0.7108707427978516,
0.5146729946136475,
0.6504074335098267,
-0.18315067887306213,
0.17158204317092896,
0.19745829701423645,
-0.416235089302063,
0.391841471195220... |
TASK DEFINITION: In this task, you need to count the number of times the given letter appears in the given sentence.
PROBLEM: Sentence: 'there are two men sitting on a couch playing video games'. Find frequency of the letter 'v'
SOLUTION: 1
PROBLEM: Sentence: 'a little dog on a table while a dog groomer cuts its fur'... | 4
| 8 | NIv2 | task113_count_frequency_of_letter | fs_opt | [
-0.668451189994812,
-0.09537234902381897,
-1.1711078882217407,
0.04860853776335716,
-0.23799023032188416,
0.785456657409668,
1.0861501693725586,
0.4820420742034912,
0.40889328718185425,
-0.398101270198822,
-0.29128342866897583,
-0.14235034584999084,
-0.11343051493167877,
0.1190139725804328... |
Q: In this task, you are given a sentence in Spanish and your task is to translate it into English. In translation, keep the numbers and capitalization (capitalize only the first word of each sentence and name).
Es el resultado del reciente conflicto y de los años de negligencia y falta de mantenimiento que lo precedie... | This results both from the recent conflict and from the years of neglect and lack of maintenance that preceded it. | 7 | NIv2 | task531_europarl_es_en_translation | zs_opt | [
-0.07359029352664948,
0.9369764924049377,
0.4494243264198303,
-0.8069896697998047,
0.17055784165859222,
-0.9743619561195374,
0.8411918878555298,
0.7097889184951782,
-0.36262983083724976,
-0.06122204661369324,
0.10974381119012833,
0.2600773572921753,
-1.0253360271453857,
0.1776268631219864,... |
Given a sentence in Italian, generate a new Italian 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 b... | Un nuovo libro da un autore favorito ti farebbe desiderare di spendere soldi.
****
| 4 | NIv2 | task408_mickey_it_sentence_perturbation_generation | fs_opt | [
0.01950289122760296,
-0.010480664670467377,
0.35775327682495117,
0.03953772410750389,
-0.04230392724275589,
-0.812322199344635,
0.8035286664962769,
1.346535563468933,
-0.5208214521408081,
-0.18396911025047302,
-0.8747624158859253,
0.17985239624977112,
-0.07334662973880768,
0.42904657125473... |
In this task you will be given a list, of lists, of numbers. Each list is presented with brackets and comma-separated values. For example, a list of numbers is [1,2,3] and a list of two lists of numbers is [[1,2],[3,4,6]]. You should sum up the values at every position of every inner list and put it as an element of yo... | [-53, -9, 166, -8, -144, -114, -11, 32]
****
| 4 | NIv2 | task122_conala_list_index_addition | fs_opt | [
-0.05373712256550789,
-0.1601754128932953,
-0.6208637952804565,
-0.42837363481521606,
0.013440914452075958,
-0.2973717749118805,
0.8784571886062622,
0.569708526134491,
-0.4793415069580078,
-0.19970858097076416,
-0.5330277681350708,
0.08052920550107956,
-0.2575926184654236,
-0.0526811815798... |
Part 1. Definition
In this task, you are given reviews written about the books in Bengali. You are expected to classify the sentiment of the reviews into two classes: positive or negative.
Part 2. Example
অসাধারণ একটি বই, লজিকাল স্কিল ডেভেলপমেন্ট এর জন্যে অতুলনীয়..
Answer: positive
Explanation: Here the reviewer seems... | negative | 7 | NIv2 | task1497_bengali_book_reviews_sentiment_classification | fs_opt | [
-1.28489351272583,
-0.1422768235206604,
0.6412248611450195,
-0.5784041881561279,
0.011239726096391678,
0.33241385221481323,
0.6773887872695923,
-0.1924961805343628,
0.5167511701583862,
-0.8144155740737915,
-1.090694785118103,
0.039086006581783295,
-0.2750995457172394,
-0.01840348355472088,... |
Given the task definition and input, reply with output. Given a sentence in Japanese, provide an equivalent paraphrased translation in Korean that retains the same meaning both through the translation and the paraphrase.
イタリアの教会St. Giovanni Boscoは、St. John Boscoにちなんで名付けられました。
| 이탈리아 성 지오 바니 보스코 교회 (St. Giovanni Bosco Church)는 성 요한 보스코 (St. | 5 | NIv2 | task814_pawsx_japanese_korean_translation | zs_opt | [
0.46832817792892456,
1.0935732126235962,
-0.6543835401535034,
-0.2801815867424011,
-0.27358564734458923,
-0.9826033115386963,
0.7052693963050842,
-0.541745662689209,
-0.22973361611366272,
-0.5871442556381226,
0.012874350883066654,
0.9017789363861084,
-0.7261921167373657,
0.8292018175125122... |
Given a sentence in Hindi, generate a new Hindi sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being... | भोजन के खाने का प्रभाव पूर्ण हो रहा है ।
| 7 | NIv2 | task407_mickey_hi_sentence_perturbation_generation | fs_opt | [
0.022032365202903748,
0.08544997870922089,
0.5355008840560913,
0.1940767765045166,
-0.3013474941253662,
-0.3934684991836548,
0.126454159617424,
0.2683730721473694,
-0.5843654870986938,
-0.8568112254142761,
-0.6769797205924988,
-0.4374240040779114,
-0.26201337575912476,
0.2527344822883606,
... |
In this task, you're given the title and three arbitrary sentences out of a five-sentence story. You are also given three additional sentence options, a, b, and c, that may or may not belong to the story. Your job is to pick the two options that seamlessly connect with the rest of the story; note that the selected choi... | Output: bc
| 2 | NIv2 | task221_rocstories_two_choice_classification | fs_opt | [
-0.05567661672830582,
0.29992425441741943,
-0.4907718300819397,
0.21396607160568237,
0.1840161234140396,
-0.36023586988449097,
0.530377984046936,
1.4123932123184204,
-0.2975689172744751,
0.14325842261314392,
-0.3576064705848694,
-0.1218816488981247,
-0.010334115475416183,
-0.52793675661087... |
Teacher:We would like you to assess the QUALITY of each of the following argument (discussing Gun Control) and determine if the argument is Valid or Invalid. A valid argument is clearly interpretable and either expresses an argument, or a premise or a conclusion that can be used in an argument for the topic of gun cont... | Valid | 6 | NIv2 | task150_afs_argument_quality_gun_control | zs_opt | [
0.35581421852111816,
0.7655065059661865,
0.7352240085601807,
-0.4776756167411804,
-0.31217432022094727,
-1.7490942478179932,
0.3750925064086914,
0.7061600685119629,
0.35891255736351013,
0.16425102949142456,
-0.4505419135093689,
-0.578881025314331,
-0.29697421193122864,
-0.00489100022241473... |
In this task, you're given a context, a sentence, and a character. The sentence describes an action or job of the given character. Also, the context provides more information about the sentence or the character. Your task is to return one of the emotions which are expressed by the Character in the given sentence. For ... | None
| 0 | NIv2 | task293_storycommonsense_emotion_text_generation | fs_opt | [
-0.014731448143720627,
0.3868493437767029,
-0.3271351456642151,
-0.022476516664028168,
-0.26166653633117676,
-0.14411216974258423,
0.6838474273681641,
0.5804643630981445,
0.15833550691604614,
-0.1808205395936966,
-0.6188336610794067,
-0.3221661448478699,
-0.428742915391922,
0.2767823934555... |
You are provided with an "Event", "Intent" and "XEmotion" (PersonX's reactions for the given "Event"). Indicate PersonY's reaction (person feels) at the end of this event. Provide one reaction for PersonY. If there's nothing that can be implied, respond as None
Event:PersonX sacrifices PersonX's ___ for the sake. Inte... | thankful | 0 | NIv2 | task924_event2mind_word_generation | zs_opt | [
0.35740146040916443,
0.35223329067230225,
0.1419806182384491,
-0.26356393098831177,
-0.976699709892273,
-0.4123396873474121,
1.0530644655227661,
0.5063861608505249,
0.20553521811962128,
-0.6075341701507568,
0.6026830673217773,
-0.11235899478197098,
-0.553786039352417,
0.4941018223762512,
... |
A text is given in Gujarati. Translate it from the Gujarati language to the Urdu language. The translation must not omit or add information to the original sentence.
Example input: તેમણે અમેઠીમાં કલાશ્નિકોવ એસોલ્ટ રાયફલનુ ઉત્પાદન કરનાર સંયુક્ત સાહસ ઇન્ડો-રશિયન રાયફલ્સ પ્રા
Example output: مشترکہ وینچر انڈو-روسی رائفلز... | اس مفاہمت نامے میں کوئی مالی مضمرات شامل نہیں ہیں۔ اس سلسلے میں تحقیق کرنے، تربیتی کورس کرنے، کانفرنسوں میٹنگوں کے انعقاد وغیرہ کیلئے آیوش کی وزارت کی موجودہ منصوبہ بند اسکیموں کے بجٹ سے ہی رقم مختص کی جائے گی۔ | 3 | NIv2 | task1001_pib_translation_gujarati_urdu | fs_opt | [
-0.46413949131965637,
0.7683019638061523,
-0.021615024656057358,
-0.6909427642822266,
0.06390631198883057,
0.07898563146591187,
0.5390591621398926,
0.6011066436767578,
0.09172338247299194,
-0.5698754787445068,
-0.9302068948745728,
-0.03541357070207596,
-0.9400621652603149,
0.14804500341415... |
Instructions: In this task, you are given Wikipedia articles on a range of topics as passages and a question from the passage. We ask you to answer the question by classifying the answer as 0 (False) or 1 (True)
Input: Passage: Jeepers Creepers 3 -- The next day, Addison says goodbye to Buddy before he leaves for a hig... | 0 | 3 | NIv2 | task1661_super_glue_classification | zs_opt | [
-0.05465995520353317,
0.14785930514335632,
-0.3576415777206421,
-0.36184602975845337,
-0.010698127560317516,
-0.542887806892395,
0.75989830493927,
-0.31706658005714417,
-0.09264182299375534,
0.030481398105621338,
0.017788603901863098,
0.21428075432777405,
0.04871905595064163,
-0.3300575017... |
Detailed Instructions: In this task, you are given a sentence from the research paper and your task is to classify the given sentence into the following categories: Background (Why is this problem important? What relevant works have been created before? What is still missing in the previous works? What are the high-lev... | method | 9 | NIv2 | task1163_coda19_section_classification | zs_opt | [
-0.40263351798057556,
0.13806897401809692,
0.3052601218223572,
-0.15534107387065887,
0.27714088559150696,
-0.6216721534729004,
0.021106943488121033,
0.4103098511695862,
0.4598865211009979,
0.09383662790060043,
-1.2015092372894287,
-0.2810286581516266,
-0.2666627764701843,
0.262092381715774... |
Detailed Instructions: You are given a statement written in Telugu. 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 .
Problem:Statement: ఈ <MASK> మూసీ నది ఒడ్డున నిర్మించబడింది. ప్రస్తుతం ఈ ప్రదేశం హైదరాబాదు నగ... | బరాదారి | 8 | NIv2 | task954_wiki_cloze_te_multiple_choice_question_answering | zs_opt | [
0.20888520777225494,
1.1920595169067383,
0.2036028504371643,
0.001773449475876987,
0.1876855343580246,
-0.6550136804580688,
-0.22542841732501984,
0.4690045118331909,
0.3321065306663513,
-0.4257315695285797,
-0.48238906264305115,
-0.4177253246307373,
-0.21220529079437256,
0.1462972760200500... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse ... | The dog is brown
| 5 | NIv2 | task184_snli_entailment_to_neutral_text_modification | fs_opt | [
-0.06328040361404419,
0.48992830514907837,
0.19230106472969055,
-0.3106437921524048,
0.3321691155433655,
-0.5677659511566162,
-0.38238340616226196,
0.25860655307769775,
0.44878455996513367,
-0.9602987766265869,
-0.40009772777557373,
-0.663447380065918,
-0.5245009660720825,
-0.0455577969551... |
Part 1. Definition
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.
Part 2. Example
... | History | 7 | NIv2 | task521_trivia_question_classification | fs_opt | [
0.3074687123298645,
0.9366697072982788,
-0.19284361600875854,
0.28341707587242126,
0.4936378300189972,
-0.12583854794502258,
0.7329980731010437,
0.6468459367752075,
0.6702170372009277,
0.0023491200990974903,
-0.5856432914733887,
0.8411927223205566,
-1.4086809158325195,
-0.4128848612308502,... |
Definition: You are given a sentence in English. Your job is to translate the English sentence into Persian.
Input: This solution was initially designed for the Chinese market, but now it's selling like hotcakes in the U.S. and Europe, where hospitals are pressured to deliver quality care at lower cost.
Output: | این راهکار ابتدا برای بازار چین طراحی شد ، ولی اکنون به سرعت در حال فروش در امریکا و اروپاست ، جایی که بیمارستان ها ملزم به ارائه بهترین کیفیت با کمترین هزینه اند. | 2 | NIv2 | task1093_ted_translation_en_fa | zs_opt | [
-0.4234914183616638,
0.6537137031555176,
-0.4808403551578522,
0.20533856749534607,
0.1921977698802948,
0.09038474410772324,
-0.10766883194446564,
1.6367579698562622,
0.8832586407661438,
0.3342515230178833,
-0.2421388328075409,
0.46202149987220764,
0.023958632722496986,
0.21269676089286804,... |
You will be given a definition of a task first, then some input of the task.
In this task, you will be presented with a 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 ... | False | 1 | NIv2 | task346_hybridqa_classification | zs_opt | [
0.00881881546229124,
0.02746644988656044,
-0.2586521804332733,
0.2845783233642578,
-0.28697237372398376,
-0.5424796938896179,
0.6216682195663452,
0.4203208386898041,
-0.35194337368011475,
-0.15427009761333466,
-0.5977387428283691,
0.2700712978839874,
-0.30850863456726074,
0.176511347293853... |
Given a passage with a question and an answer to that question, classify if the answer actually answers the question into 'yes' or 'no'. Output 'yes' if the answer answers the question and output 'no' if the answer does not answer the question.
One example is below.
Q: Question: Are group 2 innate lymphoid cells ( ILC2... | yes | 9 | NIv2 | task846_pubmedqa_classification | fs_opt | [
-0.1839287430047989,
0.5528956651687622,
-0.4575023055076599,
0.4713681638240814,
-0.17092759907245636,
-0.4432203769683838,
0.2962219715118408,
0.6608783006668091,
0.07066361606121063,
-0.06894797086715698,
-0.5841115713119507,
0.3787444531917572,
-0.6817398071289062,
0.5203198194503784,
... |
Definition: In this task, you are given a sentence from the Bible in English, and your task is to translate it into Persian.
Input: On the twelfth day Ahira the son of Enan, prince of the children of Naphtali, offered:
Output: | و بجهت ذبیحه سلامتی، دو گاو و پنج قوچ و پنج بز نر و پنج بره نرینه یک ساله. این بودهدیه اخیرع بن عینان. | 2 | NIv2 | task655_bible_en_fa_translation | zs_opt | [
0.176144078373909,
0.4934096336364746,
0.2994915544986725,
-0.4352825880050659,
-1.1971416473388672,
0.42249834537506104,
0.4111681878566742,
0.6066989898681641,
0.6085795164108276,
-0.12392012029886246,
-0.32977449893951416,
0.7782791256904602,
-0.9120100736618042,
-0.25423309206962585,
... |
Definition: You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Input: System Reference: ristorante parma near marina cow hollow offer... | 1 | 2 | NIv2 | task1186_nne_hrngo_classification | zs_opt | [
-0.14554935693740845,
0.6038588285446167,
-0.4072064757347107,
0.5121222734451294,
-0.4162568151950836,
-0.29555556178092957,
1.013505220413208,
0.9631247520446777,
-0.38766419887542725,
0.1266779899597168,
-0.17403846979141235,
0.17521312832832336,
-0.6720941066741943,
-0.0760476291179657... |
Teacher:Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid ... | Does the bifunctional dihydrofolate reductase thymidylate synthase of Tetrahymena thermophila provide a tool for molecular and biotechnology applications? | 6 | NIv2 | task845_pubmedqa_question_generation | zs_opt | [
0.5486239790916443,
1.0475268363952637,
-0.6009464263916016,
0.3279710114002228,
-0.4910788834095001,
-0.5865767002105713,
0.10083430260419846,
0.48100435733795166,
0.3249585032463074,
0.4851253032684326,
-0.40182334184646606,
0.29557421803474426,
-0.570356011390686,
0.26252710819244385,
... |
Given the task definition and input, reply with output. In this task, you're given a passage that represents a legal contract or clause between multiple parties, followed by a question that needs to be answered. Based on the paragraph, you must write unambiguous answers to the questions and your answer must refer a spe... | If Lucid accepts Distributor's order and fails to deliver ordered products, Distributors sole remedy will be limited to refund of money paid to Lucid for any undelivered products. | 5 | NIv2 | task597_cuad_answer_generation | zs_opt | [
0.12302476912736893,
0.15079259872436523,
0.22755584120750427,
-0.24708648025989532,
0.5900781154632568,
0.2566109001636505,
0.3440741300582886,
1.1635875701904297,
-0.21246619522571564,
0.17034797370433807,
-0.10563983768224716,
0.2732639014720917,
-0.5066064596176147,
0.38176900148391724... |
Detailed Instructions: In this task the focus is on physical knowledge about the world. Given the provided goal task in the input, describe a process that would lead to the asked outcome. This process often involves physical motions with objects, such as moving them, arranging them in a certain way, mixing them, shakin... | can be cured by salt during the winter | 9 | NIv2 | task080_piqa_answer_generation | zs_opt | [
-0.21029245853424072,
0.4437248706817627,
-1.0152816772460938,
0.3594914376735687,
-0.9355448484420776,
0.03920731320977211,
-1.2155306339263916,
0.39997559785842896,
-0.12778757512569427,
0.3288790285587311,
-0.2221364676952362,
0.6119853258132935,
-0.7426732778549194,
0.11987552046775818... |
Given the task definition, example input & output, solve the new input case.
You will be given a text in the Russian language, and you should classify the given input text to one of the emotion labels from this list of emotion labels- ['joy', 'sadness', 'surprise', 'fear', 'anger']. Make sure your output label (i) is s... | sadness | 1 | NIv2 | task1662_cedr_ru_classification | fs_opt | [
-0.5508440732955933,
0.4350247085094452,
-0.19911405444145203,
-0.08293569833040237,
-0.10739189386367798,
0.3240754306316376,
0.31550610065460205,
1.0573561191558838,
0.025568723678588867,
0.08625850081443787,
-0.2574169337749481,
0.2904161810874939,
0.24699798226356506,
0.393952608108520... |
In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In the translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
One example: पहले दो को अविश्वसनीय मानकर बाकी पांच मुखबिरों के आधार पर मु... | A full-grown boar weighs about 275 to 375 kilograms and an average sow weighs from 200 to 300 kilograms . | 6 | NIv2 | task424_hindienglish_corpora_hi_en_translation | fs_opt | [
-0.1671486496925354,
0.028118137270212173,
0.38072633743286133,
-0.0598442405462265,
0.17523086071014404,
0.04400297626852989,
-0.5940550565719604,
0.900995135307312,
-0.3688514530658722,
-0.2704640328884125,
-0.393368661403656,
0.0905071347951889,
-0.8509469032287598,
0.05943604186177254,... |
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 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 re... | Yes | 0 | NIv2 | task1207_atomic_classification_atlocation | fs_opt | [
0.31277087330818176,
0.4438709616661072,
0.4619750380516052,
-0.24063168466091156,
-0.41658222675323486,
-0.18686409294605255,
1.2083725929260254,
0.5434726476669312,
-0.31952786445617676,
-0.13253207504749298,
-0.17966358363628387,
-0.746687650680542,
-0.5317258834838867,
0.56016182899475... |
You will be given a definition of a task first, then some input of the task.
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the ou... | ['CASE_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'CASE_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_D... | 1 | NIv2 | task1416_youtube_caption_corrections_incorrect_grammar_classification | zs_opt | [
0.2724565267562866,
0.0005454800557345152,
0.09063779562711716,
0.036008186638355255,
0.4513999819755554,
-0.35876190662384033,
0.39823010563850403,
0.6650190353393555,
-0.35506975650787354,
0.21968677639961243,
-0.2966451942920685,
-0.8127639293670654,
-0.3423019051551819,
-0.054829277098... |
Given a story, answer the question about the story. The question is the last sentence in the input. The story has one of the three following scenarios: the first is when the individual's belief matches reality, the second is when the individual's belief does not match reality, and the third is when an individual has a ... | green_drawer
| 1 | NIv2 | task152_tomqa_find_location_easy_noise | fs_opt | [
-0.18263065814971924,
-0.3451404571533203,
-0.46133866906166077,
0.11638756096363068,
-0.14740478992462158,
-0.46364375948905945,
-0.15624262392520905,
0.5890984535217285,
-0.011615592055022717,
0.521995484828949,
-0.10777066648006439,
0.24775910377502441,
0.011864032596349716,
0.054343312... |
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.
[EX Q]: Mg squad all be safe
[EX A]: No... | Hope Speech
| 6 | NIv2 | task680_hope_edi_tamil_text_classification | fs_opt | [
-0.629160463809967,
-0.3291400074958801,
0.5742735862731934,
0.31023865938186646,
0.01705528423190117,
-0.644686222076416,
-0.5277423858642578,
0.8645597100257874,
-0.841452956199646,
0.40317410230636597,
0.07139906287193298,
-0.2669355571269989,
-0.043096352368593216,
-0.7616298198699951,... |
Given a scientific question, generate a correct answer to it.
One example is below.
Q: Who proposed the theory of evolution by natural selection?
A: darwin
Rationale: This is a direct fact that Charles Darwin proposed the theory of evolution.
Q: What is it called when the chance that a certain event will occur?
A: | probability | 9 | NIv2 | task591_sciq_answer_generation | fs_opt | [
0.2982305586338043,
0.2357003390789032,
0.03513781726360321,
-0.06145201250910759,
-0.3914320766925812,
-0.3522622585296631,
-0.7193941473960876,
-0.07772379368543625,
0.2587645649909973,
0.1963561475276947,
-0.4203946888446808,
-0.09737074375152588,
-1.1256639957427979,
-0.185385093092918... |
Detailed Instructions: In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e. tagset ... | NOUN | 8 | NIv2 | task583_udeps_eng_coarse_pos_tagging | zs_opt | [
0.7933943271636963,
0.33731693029403687,
0.001902538351714611,
-0.008517971262335777,
-0.08178341388702393,
-0.5425825119018555,
0.8858401775360107,
0.7965786457061768,
-0.38008445501327515,
-0.2144421637058258,
-0.46402978897094727,
0.03277285024523735,
-0.6305158138275146,
0.499951779842... |
Detailed Instructions: Given a statement about date and time, state whether the statement is true or false. The number of date/time operands in the statement ranges between 2 and 3. Let's say the values are denoted by t1, t2 and t3. The statements follow one of the following ten templates: 't1 occurs before t2, t1 does... | False | 8 | NIv2 | task1507_boolean_temporal_reasoning | zs_opt | [
-0.14784303307533264,
0.01623363047838211,
-0.5863132476806641,
0.5031018257141113,
-0.24940885603427887,
-0.39752399921417236,
0.33327367901802063,
1.1232404708862305,
-1.12919282913208,
0.1548783928155899,
-0.4528302252292633,
-0.4629494249820709,
0.09149537980556488,
-0.103764109313488,... |
instruction:
A text is given in English. Translate it from the English language to the Malayalam language. The translation must not omit or add information to the original sentence.
question:
Cabinet Cabinet approves reservation in Teachers Cadre Ordinance, 2019
answer:
2019-ലെ അധ്യാപക കേഡര് സംവരണ ഓര്ഡിനന്സിന് മന്ത്... | ജമ്മു കാശ്മീരിലെ ജോലികളിലും വിദ്യഭ്യാസസ്ഥാപനങ്ങളിലും സാമ്പത്തികമായി പിന്നോക്കം നില്ക്കുന്ന വിഭാഗങ്ങള്ക്ക് 10% സംവരണം വ്യാപിപ്പിക്കുന്നതാണ് ബില്.
| 9 | NIv2 | task1021_pib_translation_english_malayalam | fs_opt | [
-0.126215860247612,
0.3594355583190918,
0.3828003406524658,
-0.5329536199569702,
0.2529507279396057,
-1.0324909687042236,
-0.16826418042182922,
0.2759678065776825,
-0.3072182536125183,
0.27446889877319336,
0.23779767751693726,
-0.5183627009391785,
0.03020286187529564,
-0.21571314334869385,... |
Decide the language of that sentence. The language can be English, French, German, Italian, or Spanish.
Example Input: Text: 'Oui, j'ai besoin d'un schema'
Example Output: French
Example Input: Text: 'para el día dieciséis de junio .'
Example Output: Spanish
Example Input: Text: 'Commençons par ça oui. Les moules on... | French
| 3 | NIv2 | task896_miam_language_classification | fs_opt | [
0.32021674513816833,
0.6608190536499023,
0.22352996468544006,
-0.40475568175315857,
-0.29647403955459595,
-0.4161730110645294,
-0.21291959285736084,
0.9936270713806152,
-0.11692684143781662,
-0.4752025008201599,
0.10247369110584259,
0.1701207160949707,
0.05766576901078224,
-0.4003862738609... |
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