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 are given two strings A,B. Find the longer of the two lists, convert it to lowercase, and return all the unique alphabets used in it. The two input strings are never equal.
AMGjatkgCe, OCsTatkgYfHl
| a, c, f, g, h, k, l, o, s, t, y | 5 | NIv2 | task756_find_longert_substring_and_return_all_unique_alphabets_in_it | zs_opt | [
-0.35496872663497925,
1.1693615913391113,
0.020689338445663452,
-0.3209228813648224,
0.3330079913139343,
-0.5920591950416565,
0.913006067276001,
-0.7224178910255432,
-0.03430158644914627,
-0.16557221114635468,
-0.9294586181640625,
-0.42766430974006653,
0.4199806749820709,
-0.22298336029052... |
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 The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ).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... | No | 9 | NIv2 | task1205_atomic_classification_isafter | zs_opt | [
0.27023863792419434,
0.5782042741775513,
0.453352153301239,
-0.30283021926879883,
-0.5733652114868164,
-0.9811033010482788,
0.8895710706710815,
0.46903061866760254,
-0.6657606363296509,
-0.46618154644966125,
-0.3789631724357605,
-0.2960313558578491,
-0.6743841767311096,
0.23454520106315613... |
In this task, you are given a premise, a hypothesis, and an update. The premise sentence describes a real-world situation and is always assumed to be true. The hypothesis sentence describes an assumption or inference that you might make about that situation having read the premise. The update provides additional inform... | strengthener | 3 | NIv2 | task936_defeasible_nli_snli_classification | fs_opt | [
0.49683910608291626,
0.29282286763191223,
-0.5668116807937622,
0.026693198829889297,
0.012715213000774384,
-0.7242802381515503,
0.8768867254257202,
1.183881402015686,
0.8874158263206482,
-0.17362487316131592,
-1.173782229423523,
0.23807738721370697,
-0.5996077060699463,
0.14059939980506897... |
Detailed Instructions: In this task, you are given a sentence that is either in the Yoruba language or the English language. Your task is to identify the language of the input sentence. Input sentences should be in Yoruba or English language and also it cannot have two languages at a time.
See one example below:
Proble... | English | 4 | NIv2 | task1621_menyo20k-mt_en_yo_language_identification | fs_opt | [
0.5729899406433105,
0.34212836623191833,
0.7586454153060913,
-0.24000000953674316,
0.154867023229599,
-0.9801923632621765,
0.2537422776222229,
0.08738625049591064,
0.5781542062759399,
-0.435295045375824,
0.08224888145923615,
0.4281378984451294,
-0.21248671412467957,
-0.17777061462402344,
... |
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 find all the elements of the list that are numbers in the same order as they appear in the list A.
['3305', 'V', '3443', '7105', '235', 'g', '4791', 'J', 'y', 'Y', '5367', '9413', '5301... | 3305, 3443, 7105, 235, 4791, 5367, 9413, 5301 | 1 | NIv2 | task497_extract_all_numbers_from_list_in_order | zs_opt | [
-0.5873751044273376,
-0.08874985575675964,
-0.5324060916900635,
-0.12122263014316559,
0.14007316529750824,
0.3237881064414978,
0.04873216897249222,
-0.19938364624977112,
-0.026628199964761734,
0.12838837504386902,
-0.7651876211166382,
-0.6496773958206177,
0.10111892968416214,
0.02253240160... |
In this task, you are given a sentence in the Spanish language. Your task is to translate the Spanish sentence into the English language.
Example input: Placa motora es la unión entre la neurona motora y el
Example output: Motor plate is the union between the motor neuron and the
Example explanation: Language translat... | Vasconstricts systemic arterioles | 3 | NIv2 | task1433_head_qa_language_translation_es_to_en | fs_opt | [
-0.020103637129068375,
-0.04703005403280258,
0.5113719701766968,
0.08484223484992981,
0.21423032879829407,
-1.1133761405944824,
0.42527565360069275,
0.7579176425933838,
0.6360883712768555,
-0.08753098547458649,
0.05106993764638901,
0.5361852049827576,
-0.043774910271167755,
0.1335568428039... |
Q: Given a sentence in the Japanese, provide an equivalent translation in Lao that retains the same meaning through the translation. In translation, keep numbers as it is.
地球全体の地表温度は記録上もっとも温かかったが、一方海表温度は1997年から1998年のエル・ニーニョ現象の間に打ち立てられた記録より摂氏で約0.06度低く、過去128年間で2番目に温かい記録と並んだ。
A: | ອຸນຫະພູມໜ້າດິນໃນທົ່ວໂລກແມ່ນຮ້ອນທີ່ສຸດຈາກການບັນທຶກ ໃນຂະນະທີ່ ອຸນຫະພູມໜ້າມະຫາສະໝຸດ ຮ້ອນສຸດຄັ້ງທີສອງໃນຊ່ວງໄລຍະ 128 ປີທີ່ຜ່ານມາ ປະມານ 0.06 ອົງສາ ເຢັນຂຶ້ນກວ່າການບັນທຶກທີ່ໄດ້ບັນທຶກໃນໄລຍະທີ່ ເອລ ນີໂຢ ເຂັ້ມແຂງ ໃນປີ 1997-1998. | 7 | NIv2 | task1124_alt_ja_lo_translation | zs_opt | [
0.16374972462654114,
0.4392277002334595,
-0.43855008482933044,
-0.1448901891708374,
-0.2865852117538452,
-1.294034481048584,
-0.4753575623035431,
0.06547924876213074,
-0.13977399468421936,
-0.3927997946739197,
-0.13830165565013885,
0.5349097847938538,
-0.8625562191009521,
0.738851368427276... |
In this task you are given a list of triplets of the form [subject, predicate, object] and the output should be a question based on the triplets but with the subject and/or object replaced with blanks (represented using two or more consecutive underscores). Triplet values encompassed in [*] are special tokens that can ... | if you are looking for a place that is _____t child friendly that serves English food and in the high price range then there is a place called _____ | 6 | NIv2 | task1407_dart_question_generation | fs_opt | [
-0.5218707323074341,
0.2517058849334717,
-0.3644563853740692,
-0.1874023824930191,
-0.07747016847133636,
0.07701282203197479,
0.7931682467460632,
0.5418453812599182,
-0.0372023843228817,
-0.16071081161499023,
-0.4381769597530365,
-0.05327949672937393,
-0.4746251702308655,
-0.52692687511444... |
Part 1. Definition
Given a story, answer the question about the story. The question is the last sentence in the input. These stories can be difficult due to their length and how each story has at least one of the three following scenarios: the first is when the individual's belief matches reality, the second is when th... | red_drawer | 7 | NIv2 | task154_tomqa_find_location_hard_noise | fs_opt | [
-0.025660566985607147,
-0.22739198803901672,
-0.26492568850517273,
-0.007536574266850948,
-0.10157191008329391,
-0.4997754991054535,
0.5208748579025269,
0.39034727215766907,
0.06531976163387299,
0.06254363805055618,
-0.08733100444078445,
0.685221254825592,
-0.07651213556528091,
0.120659381... |
Q: In this task, you need to reverse all words of a given length in the sentence. The number of letters in a word determine its length. For example, the length of the word "apple" is 5.
Sentence: 'a grass area with rocks on it and several zebra grazing in the grass with trees in the background'. Reverse all words of le... | a grass aera htiw rocks on it and several zebra grazing in the grass htiw trees in the background | 7 | NIv2 | task378_reverse_words_of_given_length | zs_opt | [
0.14060290157794952,
1.1424946784973145,
0.0037608412094414234,
-0.6186144351959229,
-0.3507818579673767,
-0.7584860324859619,
0.48507553339004517,
0.22300434112548828,
0.02288234233856201,
-0.6291095614433289,
-1.1961257457733154,
-0.05451585352420807,
-0.33549678325653076,
-0.24479445815... |
Definition: In this task, you are given a sentence in Persian, and your task is to translate it into English.
Input: گفتگوی حریفی زرنگ و فرهیخته دایما سراسر زندگی گذشتهاش را از نظر خویش میگذراند،
Output: | the conversation of a clever, cultured man that Martin kept seeing himself down all his past. | 2 | NIv2 | task660_mizan_fa_en_translation | zs_opt | [
-0.3431113362312317,
0.38477152585983276,
-0.20467180013656616,
-0.3402706980705261,
-0.1426447331905365,
0.4026843309402466,
1.0253994464874268,
-0.6590232253074646,
0.7445678114891052,
-0.15506932139396667,
-1.2334429025650024,
0.3501186966896057,
-0.28849607706069946,
0.4790616631507873... |
Given the task definition and input, reply with output. In this task, you will be given a list of numbers. The goal is to divide all the numbers in the list by a constant such that the sum of the resulting list is 1. The output should be rounded to 3 decimals.
[-35.26, -27.819, -90.972, 118.35, -78.672]
| [ 0.308 0.243 0.795 -1.035 0.688] | 5 | NIv2 | task093_conala_normalize_lists | zs_opt | [
-0.8768654465675354,
0.6990185976028442,
-0.45826542377471924,
-0.9005194902420044,
-0.05380798503756523,
0.4409712851047516,
0.6017193794250488,
-0.5171984434127808,
-0.18865762650966644,
-0.2697349190711975,
-0.7902718782424927,
0.44823431968688965,
-0.306343138217926,
-0.033069822937250... |
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 e... | Yes | 9 | NIv2 | task1203_atomic_classification_xreact | zs_opt | [
0.14744144678115845,
0.3342067003250122,
0.46760839223861694,
-0.32093220949172974,
-0.5421484708786011,
-1.4433708190917969,
1.331913948059082,
0.6049436926841736,
-0.640885055065155,
-0.5007949471473694,
-0.3016818165779114,
-0.19634708762168884,
-0.7866806983947754,
0.42606818675994873,... |
Instructions: You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. If the conversation begins with a question, label it '1' otherwise '0'.
Input: Person1: Well , it was nice meeting you .
Person2: Yes , I hope we meet again .
Person1: ... | 0 | 3 | NIv2 | task1534_daily_dialog_question_classification | zs_opt | [
-0.11999234557151794,
0.6067895889282227,
-0.3187844753265381,
0.14735907316207886,
0.1986939013004303,
-0.6514226198196411,
0.41763126850128174,
-0.5415616035461426,
0.33751219511032104,
0.30584603548049927,
-0.5613843202590942,
-0.5341840982437134,
-0.016938913613557816,
-0.0652225390076... |
In this task, you are given a multiple-choice question about healthcare. Answer the question based on your information and classify your answers into '1', '2', '3', and '4'.
Example: Question: A 13-year-old girl is operated on due to Hirschsprung illness at 3 months of age. Which of the following tumors is more likely ... | Solution: 2 | 5 | NIv2 | task1431_head_qa_answer_generation | fs_opt | [
-0.05599471181631088,
0.41173458099365234,
-0.21613605320453644,
0.05352356657385826,
-0.30979809165000916,
0.1717921793460846,
0.06557074189186096,
0.846514105796814,
-0.28196007013320923,
0.7141060829162598,
-0.523823618888855,
-0.09390276670455933,
0.141478031873703,
0.06626637279987335... |
In this task, you will be presented with a question in Dutch language, and you have to write the named entities from the question if present. B denotes the first item of a phrase and an I any non-initial word. Here is the list of terms used: person names (PER), organizations (ORG), locations (LOC) and miscellaneous nam... | None
| 5 | NIv2 | task1544_conll2002_named_entity_recognition_answer_generation | fs_opt | [
-0.20899838209152222,
0.541669487953186,
0.4017893075942993,
-0.07149836421012878,
-0.3313925862312317,
-0.2832251489162445,
1.156997561454773,
-0.21711859107017517,
0.42971158027648926,
-0.3542056977748871,
-0.9094284772872925,
0.5129727125167847,
-0.18384382128715515,
0.205938458442688,
... |
instruction:
You are given a target profession, and two sentences. Your task is to determine whether the second sentence is either a stereotype, anti-stereotype, or is unrelated with respect to the first sentence and the target. A stereotype is a widely held but oversimplified notion of a group of people. An anti-stere... | anti-stereotype
| 9 | NIv2 | task319_stereoset_classification_profession | fs_opt | [
-0.5083140730857849,
0.5597874522209167,
0.2605166435241699,
0.04900243133306503,
0.48736289143562317,
-0.092405304312706,
-0.11087337881326675,
1.4051594734191895,
0.6242690682411194,
0.36212947964668274,
-0.31282705068588257,
0.11602041870355606,
-0.7140742540359497,
-0.3603317141532898,... |
In this task, you are given a sentence in Persian, and your task is to translate it into English.
Q: مگ به مادرش تکیه داده و خیلی ناراحت بهنظر میرسید،
A: | Meg leaned against her mother, looking the image of despair, | 4 | NIv2 | task660_mizan_fa_en_translation | zs_opt | [
-0.5805569887161255,
0.5926705598831177,
-0.46414726972579956,
-0.9608072638511658,
-0.19948044419288635,
-0.014077278785407543,
0.9232393503189087,
0.8243676424026489,
0.5380786657333374,
-0.018492653965950012,
-0.5565140247344971,
0.21552309393882751,
-0.09249536693096161,
0.325254857540... |
Detailed Instructions: In this task you are given a list of numbers and you need to find the average of each two consecutive values. The average of two numbers a and b is calculated as: (a + b) /2. The output should be a list of the averages of each two consecutive values. A list is presented with two brackets and comm... | [21.0, 48.5, 31.5, 33.5, 78.0, -6.0, -42.0, -54.0, -54.0] | 8 | NIv2 | task124_conala_pair_averages | zs_opt | [
-0.6459084749221802,
0.051157332956790924,
-0.8635849356651306,
-0.4833637773990631,
0.10105790942907333,
0.4457671642303467,
0.882226288318634,
0.5764926671981812,
-0.10166039317846298,
-0.007021436933428049,
-0.5314836502075195,
-0.4358842372894287,
0.14582759141921997,
0.433933615684509... |
Given a sentence in the Indonesian(Bahasa variant), provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Q: Berita Utama koran seperti "gaya rambut Barat. . telah dilarang" mengulang kembali status hukum gaya rambut Barat; tukang cuk... | 「西洋のヘアースタイルは．．．禁止された」というような新聞の見出しが西洋のヘアースタイルの法的なステータスを繰り返し言及した；当局が非イスラム的なヘアースタイルだとみなすものを提供したり、メーキャップサービスを行ったり、眉を剃ったりした床屋はライセンスの長期停止や取り消しを受けることになると警告された。 | 4 | NIv2 | task1116_alt_id_ja_translation | zs_opt | [
-0.15480779111385345,
0.5502027869224548,
0.0776081308722496,
-0.45245546102523804,
-0.1306573450565338,
-0.2513952851295471,
-0.20225828886032104,
0.922031044960022,
-0.40468037128448486,
-0.11142006516456604,
-0.5170290470123291,
0.1375022828578949,
-0.4362972378730774,
0.314513415098190... |
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 of this corpus is 'ADJ'... | DET
| 5 | NIv2 | task583_udeps_eng_coarse_pos_tagging | fs_opt | [
0.9146800637245178,
0.40441399812698364,
-0.0978357195854187,
-0.2427724003791809,
0.07790181785821915,
-0.4580897092819214,
0.7866479754447937,
0.9407268762588501,
-0.4621428847312927,
-0.15735872089862823,
-0.2400265634059906,
0.1767498254776001,
-0.41971004009246826,
0.487928569316864,
... |
Given a real-life anecdote of a complex ethical situation, identify who is wrong here. Classify each post into the following categories : AUTHOR (if the author of the post is wrong in the situation), OTHER (if any of the others mentioned in the paragraph is wrong), EVERYBODY (if everyone mentioned is wrong) and NOBODY ... | NOBODY | 9 | NIv2 | task498_scruples_anecdotes_whoiswrong_classification | fs_opt | [
-0.11482249945402145,
0.06775470077991486,
-0.1695765256881714,
0.6778361797332764,
0.1543605476617813,
-0.3010600805282593,
0.02798289805650711,
0.23214417695999146,
0.4116503596305847,
0.011271069757640362,
-0.29432612657546997,
0.23658402264118195,
-0.8516082763671875,
-0.14305216073989... |
You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Farsi.
Input: Consider Input: Singapura propõe-se produzir, até 2060, [900] milhões de litros por dia de água dessalinizada.
Output: سنگاپور برای سال ۲۰۶۰ روزانه به ۹۰۰ میلیون لیتر به اب شیرین نیاز دارد سنگاپور برای سال ۲۰۶۰... | Output: پس من فکر می کنم که خیلی از کارهای فکری از این مسئله تأثیر می گیرند.
| 2 | NIv2 | task1282_ted_translation_pt_fa | fs_opt | [
-0.5005030632019043,
0.9158653020858765,
0.16745607554912567,
-0.8586630821228027,
-0.6198290586471558,
-0.645721971988678,
-0.248338520526886,
0.05989106371998787,
0.37513577938079834,
0.2747042179107666,
-0.1033378392457962,
0.5363376140594482,
-0.8023635745048523,
-0.19977760314941406,
... |
You are given a sentence in Persian. Your job is to translate the Farsi sentence into Spanish.
Q: اکنون ببینید این عدد بسیار کمه ، درمقابل تعداد لیوان های کاغذی که هرروز مصرف می کنیم ، این عدد ۴۰ میلیون لیوان درهرروز ، برای نوشیدنی های گرم که در بیشتر موارد قهوه است.
A: Pero este número no es nada comparado con... | Queremos que cuentes una historia, pero que cuentes 'nuestra' historia "". Vean, cuando yo era niño y mi padre me atrapaba en alguna mentira -y ahí está él mirándome como solía hacerlo- decía: "" Hijo, hay tres lados en cada historia.
****
| 4 | NIv2 | task1267_ted_translation_fa_es | fs_opt | [
-0.4380357265472412,
0.8589891195297241,
-0.3114379942417145,
-0.24044805765151978,
-0.8753528594970703,
-0.2519966959953308,
0.733491063117981,
0.46736234426498413,
0.10574759542942047,
-0.5372778177261353,
-0.6164143681526184,
0.268520325422287,
-0.5262412428855896,
0.11311477422714233,
... |
instruction:
In this task you are given a sentence with one coordinating conjunction (for, and, nor, but, or, yet, and so). You must judge whether the order of two coordinated clausal conjoints have been inverted or not. Inversion would result in the sentence sounding unnatural. Label the instances as "Original" or "In... | Inversion
| 9 | NIv2 | task516_senteval_conjoints_inversion | fs_opt | [
-0.7490231990814209,
0.7422447204589844,
0.48413050174713135,
-0.19629335403442383,
0.18850991129875183,
-0.9131010174751282,
0.40416663885116577,
0.7634204626083374,
-0.14832578599452972,
-0.2713167667388916,
-0.4721806049346924,
-0.5251450538635254,
-0.697342574596405,
-0.279866635799407... |
Teacher: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.
Teacher: Now, understand the problem? Solve ... | telephone | 6 | NIv2 | task197_mnli_domain_answer_generation | zs_opt | [
-1.0646016597747803,
0.1976226568222046,
0.21223917603492737,
-0.23679928481578827,
0.31661880016326904,
-0.33532342314720154,
-0.2063595950603485,
0.8835997581481934,
-0.10166339576244354,
-0.09544621407985687,
-0.4422460198402405,
-0.10632980614900589,
-0.5037178993225098,
-0.69840633869... |
You are given a sentence in Polish. Your job is to translate the Polish sentence into Galician.
One example: Dzisiaj, w Szwecji i innych bogatych krajach ludzie używają mnóstwo najróżniejszych urządzeń.
Solution is here: Hoxe, en Suecia e outros países ricos, a xente usa moitas máquinas diferentes.
Explanation: The Pol... | Cando toman as menciñas contra o VIH estas son boas para diminuír o virus no sangue e aumentar o reconto de células CD4. | 6 | NIv2 | task1261_ted_translation_pl_gl | fs_opt | [
-0.7981944680213928,
0.8415873050689697,
-0.778186559677124,
-0.2803823947906494,
-0.2499343603849411,
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1.0445250272750854,
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0.21992284059524536,
-0.21360573172569275,
-0.8444496989250183,
0.9580699801445007,
-0.4932880401611328,
-0.0214921236038208,
... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a summary for US Congressional and California state bill, your task is to generate a Title for this bill. The preferred titles are under forty words and mention the purpose of the bill.
Timely Repatriation Act - Di... | Timely Repatriation Act | 1 | NIv2 | task1659_title_generation | zs_opt | [
-0.22446848452091217,
0.6384766101837158,
0.05210665985941887,
0.44801265001296997,
0.11284417659044266,
-0.2770947217941284,
0.6335511803627014,
0.6508200168609619,
-0.6356230974197388,
0.8623999357223511,
0.10583925247192383,
0.4158386290073395,
-0.4172096848487854,
0.4800183176994324,
... |
In this task, you are given a context, a subject, a relation, and many options. Based on the context, from the options select the object entity that has the given relation with the subject. Answer with text (not indexes).
Context: The 35th Cannes Film Festival was held on May 1426. The Palme d'Or was jointly awarded t... | yugoslavia | 0 | NIv2 | task1296_wiki_hop_question_answering | zs_opt | [
0.4896503686904907,
0.10616631805896759,
-0.16296936571598053,
-0.014200113713741302,
0.7127170562744141,
0.1343446969985962,
0.913356363773346,
0.9555740356445312,
-0.5231752395629883,
0.6259802579879761,
-0.10556898266077042,
0.09692147374153137,
-0.8191457390785217,
0.6941988468170166,
... |
In this task, you are given two sets, and a question. You need to find whether an element is at the intersection of two given sets. A Set is shown by two curly braces and comma-separated numbers inside, like {1, 2, 3}. The intersection of two given sets is the largest set which contains all the elements that are commo... | No | 8 | NIv2 | task245_check_presence_in_set_intersection | fs_opt | [
0.6404211521148682,
-0.14784589409828186,
-0.4832667410373688,
0.48746147751808167,
-0.1181674376130104,
-0.8642836809158325,
0.9145656824111938,
0.6415510773658752,
-0.46922916173934937,
-0.06526732444763184,
-0.37252098321914673,
-0.04323462024331093,
0.164844810962677,
-0.14114378392696... |
Instructions: 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.
Input: Sentence: xname is a Japanese food providing pub that is less th... | cuisine[Japanese], price[less than £20], familyFriendly[yes] | 3 | NIv2 | task1597_nyc_slot_filling | zs_opt | [
-0.8484483957290649,
0.6312124729156494,
-0.5417150259017944,
-0.4356866776943207,
-0.6746395826339722,
0.33513376116752625,
0.8553634881973267,
0.32187187671661377,
0.2560194730758667,
-0.5331672430038452,
0.39919179677963257,
-0.2975831925868988,
-0.6499949097633362,
0.0790296196937561,
... |
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 Italian.
Tak samo może być z życiem tego rodzaju, z życiem na zimnych obiektach. Możliwe, że w kosmosie jest pospolite, ale go nie odkryliśmy, tylko dlatego... | La stessa cosa potrebbe esser vera per questo tipo di vita sugli oggetti freddi. Potrebbe infatti essere molto diffusa nell'intero universo e non è stata rilevata solo perché non ci siamo preoccupati di cercarla. | 1 | NIv2 | task1262_ted_translation_pl_it | zs_opt | [
-0.5481318235397339,
1.094625473022461,
-0.019718678668141365,
-0.18507203459739685,
-0.04321290925145149,
-0.3412104547023773,
0.9284910559654236,
0.08227288722991943,
-0.16283810138702393,
-0.17857718467712402,
-0.2139437198638916,
0.32199448347091675,
-0.6309481859207153,
0.284661680459... |
Write a fact related to the given fact, based on the given topic word. Note that, your fact should have at least one word in common with the given fact. All facts in this task refer to scientific facts. Your related fact must form a chain with the given fact. Chains form when two facts connect together to produce the t... | Satellite technology is a synchronous learning technology. | 4 | NIv2 | task037_qasc_generate_related_fact | zs_opt | [
-0.38110601902008057,
1.1380369663238525,
-0.7172647714614868,
-0.2898522615432739,
-0.37685179710388184,
-0.9381824731826782,
0.10145209729671478,
0.8129748106002808,
-0.5527446269989014,
0.06265236437320709,
-1.3530807495117188,
0.9648888111114502,
-0.019189894199371338,
0.10146164894104... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to choose whether the two sentences clearly agree (entailment)/disagree (contradiction) with each other, or if this cannot be determined (neutral). Your answer must be in the form of the numbers 0 (entailment), 1 (neutral), or 2(cont... | 2 | 3 | NIv2 | task1612_sick_label_classification | fs_opt | [
-0.32183024287223816,
0.35356414318084717,
0.039908286184072495,
-0.48185670375823975,
0.07768017053604126,
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-0.23973318934440613,
-0.15719415247440338,
0.039146773517131805,
-0.174788832664... |
Detailed Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Spanish.
See one example below:
Problem: فالفرقة الأولى من أجهزة الحاسب سيتم تشغيلها هذا الصيف و نحن نساعد د. زنفلر في صنع استراتيجيات حول كيفية امكانية ربط الفصل مع البيت ليمتد التعليم الى بعد اليوم المدرسي.
So... | El perro o el bebé es un canal social a la persona, y pueden notar cómo responden si están abiertos a hablar más. | 4 | NIv2 | task1232_ted_translation_ar_es | fs_opt | [
-0.5000349283218384,
0.5614528656005859,
-0.481228232383728,
-0.3556130826473236,
-0.5599246621131897,
-0.04425712674856186,
1.2026450634002686,
0.7176156044006348,
0.37762123346328735,
-0.024017874151468277,
-0.3493056893348694,
0.3358704447746277,
-0.9589619040489197,
-0.1724823862314224... |
Q: You are given a sentence in Persian. Your job is to translate the Farsi sentence into Portugese.
و.ک.: دوازده وات.
A: | WK: 12 watts. | 7 | NIv2 | task1273_ted_translation_fa_pt | zs_opt | [
-0.2156583070755005,
1.0077776908874512,
-0.5096959471702576,
-0.26580631732940674,
-1.1361985206604004,
0.23878301680088043,
0.6404443383216858,
0.5416675209999084,
1.107189416885376,
-0.7306472659111023,
-0.11965090781450272,
0.5878089666366577,
-0.07497956603765488,
0.447886198759079,
... |
In this task, you're given the middle and ending of a three-part story. Your job is to complete the short story by writing a probable beginning of the story. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a child. Avoid using any irrelevant extra information when creating ... | The Deet's decided to buy a dog.
| 7 | NIv2 | task072_abductivenli_answer_generation | fs_opt | [
0.4230373799800873,
0.8913112282752991,
-0.17705941200256348,
-0.5788317918777466,
-0.43164607882499695,
-0.07040379196405411,
0.26841670274734497,
0.4229274392127991,
-0.12182526290416718,
-0.7195469737052917,
-0.6936737298965454,
0.501264214515686,
-0.37028735876083374,
-0.04030936211347... |
In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Let me give you an example: We evaluate the proposed approach on the Chinese social media text summarization task, based on the sequence-to-sequence model. ... | LastStateRNN AvgRNN AttentionRNN | 8 | NIv2 | task460_qasper_answer_generation | fs_opt | [
-0.4640248119831085,
0.10400140285491943,
-0.013737784698605537,
-0.5286251306533813,
0.0005200197920203209,
0.1887512505054474,
0.5806732177734375,
0.29472261667251587,
-0.07651197910308838,
0.09919501841068268,
-0.7302627563476562,
0.6975187659263611,
-0.7321560382843018,
0.7138379812240... |
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 and how they appear in th... | what color is the object in the forefront of the image | 0 | NIv2 | task184_break_generate_question | zs_opt | [
0.8129185438156128,
-0.45353472232818604,
-0.7038853764533997,
0.40304386615753174,
0.4277797341346741,
-0.0903700441122055,
0.9672499895095825,
0.479152113199234,
-0.5529787540435791,
0.706434428691864,
-0.4376394748687744,
0.3484298586845398,
0.2125272899866104,
-0.0022693430073559284,
... |
You will be given a definition of a task first, then some input of the task.
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.
It's not bad, ... | Good Review | 1 | NIv2 | task929_products_reviews_classification | zs_opt | [
-0.9291176199913025,
-0.18135219812393188,
0.11575983464717865,
0.21637612581253052,
0.46145230531692505,
-0.6072958707809448,
0.6358299255371094,
0.7872937917709351,
0.024884691461920738,
0.5985016822814941,
-0.3776276409626007,
-0.11829220503568649,
-0.22907570004463196,
-0.1964516341686... |
You will be given a sentence. Check whether the sentence is grammatically correct and is meaningful. If the sentence is grammatically correct, then answer with '1', otherwise answer with '0'.
Who do you think Mary said John likes? | 1 | 0 | NIv2 | task1346_glue_cola_grammatical_correctness_classification | zs_opt | [
0.20214372873306274,
1.044884204864502,
-0.4433019161224365,
-0.4584232270717621,
-0.0958017110824585,
-1.2438918352127075,
0.40432560443878174,
0.12042199075222015,
0.3183732330799103,
-0.21059028804302216,
-0.6458368301391602,
-0.8452767729759216,
-0.12920376658439636,
-0.396710693836212... |
Detailed Instructions: 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\*.
Problem:who does ... | Ronald Leibman | 8 | NIv2 | task582_naturalquestion_answer_generation | zs_opt | [
-0.04901330918073654,
0.696806013584137,
0.44394436478614807,
-0.22192445397377014,
-0.6087616682052612,
-0.5852910876274109,
1.2554312944412231,
0.22251984477043152,
0.45055049657821655,
-0.37514200806617737,
-0.4084145426750183,
0.10126695036888123,
-1.3608222007751465,
-0.41167560219764... |
You are given a paragraph, with numbered sentences, and a question. Write the numbers of the sentences needed to answer the given question. Separate multiple sentence numbers with a comma (", "). E.g. "1, 2" would be the correct response if Sent 1 and Sent 2 are needed to answer the given question (do not include sente... | 11.
****
| 4 | NIv2 | task049_multirc_questions_needed_to_answer | fs_opt | [
0.4457499086856842,
0.22887054085731506,
-0.3948359191417694,
-0.2741762101650238,
0.5842151641845703,
-0.19206443428993225,
0.6283738613128662,
0.9796584844589233,
-0.30792373418807983,
-0.22022831439971924,
-0.4795597195625305,
0.29007887840270996,
-0.6620850563049316,
0.2357376664876938... |
Part 1. Definition
In this task, you are given a sentence in the Swedish language and a corresponding English translation of the Swedish sentence. Your task is to generate a label "Yes" if the translation is correct, otherwise generate label "No".
Part 2. Example
Swedish: Jag förklarar debatten avslutad.
English: The... | No | 7 | NIv2 | task314_europarl_sv-en_classification | fs_opt | [
-0.7217117547988892,
0.3815959095954895,
0.6617684364318848,
0.2418484091758728,
0.08210565149784088,
-0.17720723152160645,
0.9971060752868652,
0.3779831528663635,
0.5266322493553162,
-0.20532140135765076,
0.3091546595096588,
1.1055219173431396,
-0.5844491720199585,
0.25679969787597656,
... |
Q: 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.
Jamel found himself in a gloomy situation.
A: | sadness | 7 | NIv2 | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | zs_opt | [
-0.978354811668396,
0.6726046800613403,
0.8915725350379944,
-1.4555027484893799,
-0.2934596538543701,
0.114485003054142,
1.0210167169570923,
0.9381734728813171,
-0.09800232201814651,
-0.2504127621650696,
-0.39527344703674316,
-0.5383574366569519,
-0.8275870084762573,
-0.4066065847873688,
... |
Given the task definition, example input & output, solve the new input case.
Given a sentence in Spanish, generate a new Spanish 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 ... | Es necesario depositar un billete de película con el fin de ver una película. | 1 | NIv2 | task417_mickey_es_sentence_perturbation_generation | fs_opt | [
-0.4512346386909485,
0.5187307596206665,
-0.2840766906738281,
0.037068068981170654,
0.06482747197151184,
-0.374687135219574,
-0.024325620383024216,
1.3949666023254395,
0.17017525434494019,
-0.6808130145072937,
-0.3290465474128723,
-0.05797389894723892,
-0.03037187084555626,
-0.264364898204... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given two natural language statements with similar wording. You must choose the statement that makes less sense based on common sense knowledge. A '
' separates the statements. Use "first" or "second" to indicate which se... | first | 1 | NIv2 | task291_semeval_2020_task4_commonsense_validation | zs_opt | [
-0.31612032651901245,
0.4670417904853821,
-0.4656747579574585,
0.17174109816551208,
-0.2590782046318054,
0.032319076359272,
0.43747204542160034,
0.3943629562854767,
0.20677196979522705,
-0.10559561848640442,
-0.3841526508331299,
-0.5797245502471924,
-0.42129766941070557,
-0.282389879226684... |
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? If you are still confused, see the following example:
سم ، خوبي ، تو حالت خوبه .
Solution: sam . alright , youre alright .
Reason: This is a good example. The above sentence i... | why isnt she moving shes dead . | 2 | NIv2 | task659_tep_fa_en_translation | fs_opt | [
0.30721816420555115,
0.4712942838668823,
0.13467979431152344,
-1.0494126081466675,
-0.04669641703367233,
-1.204688549041748,
0.26506251096725464,
0.6715821027755737,
0.29296067357063293,
0.5678555965423584,
0.10511704534292221,
1.045442819595337,
-0.713667631149292,
-0.2512276768684387,
... |
In this task, you are given a premise and hypothesis. The task is to classify them into three categories: 'positive' if the hypothesis supports the premise, 'negated' if it opposes the premise, and 'neutral' if it neither supports nor opposes it.
Example: 'Premise : All ten guys that proved to boast were divorcing.','H... | Solution: negated | 5 | NIv2 | task1516_imppres_naturallanguageinference | fs_opt | [
-0.09991452842950821,
0.27934831380844116,
-0.23072069883346558,
-0.09365139901638031,
0.09125284850597382,
-1.1626347303390503,
0.5374115705490112,
0.6175716519355774,
0.3678472638130188,
-0.5413684844970703,
-1.1672290563583374,
0.14201587438583374,
-0.27700841426849365,
-0.9376437067985... |
In this task, you are given a second sentence. Your task is to generate the first sentence on the same topic but incoherent and inconsistent with the second sentence.
Q: However , the way in which the sporangia of Sartilmania turn upwards and their spatulate rather than reniform ( kidney - like ) shape distinguish the ... | Sartilmania has similarities with the genus Renalia . | 4 | NIv2 | task550_discofuse_sentence_generation | zs_opt | [
-0.31027114391326904,
0.5797905921936035,
-0.5421754121780396,
-0.0028984290547668934,
-0.13988704979419708,
-0.4373387098312378,
0.29648029804229736,
-0.10065852105617523,
0.18704073131084442,
-0.3260226845741272,
0.8522049784660339,
0.9547417759895325,
-1.132544994354248,
0.2966601848602... |
Detailed Instructions: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, t... | Sentence 1: The patient didn't look good, so we requested the complex charts over the diagnostics as the _ were involved.
Answer1: charts.
Sentence 2: The patient didn't look good, so we requested the complex charts over the diagnostics as the _ were skimming.
Answer2: diagnostics. | 9 | NIv2 | task029_winogrande_full_object | zs_opt | [
0.4928860664367676,
0.29430457949638367,
0.043618690222501755,
-0.2922976613044739,
0.786840558052063,
-0.8587132692337036,
0.422346830368042,
1.1487019062042236,
-0.7485877275466919,
-0.0976574718952179,
-0.26442721486091614,
0.026898864656686783,
-0.5935293436050415,
-0.16184157133102417... |
Your task is to generate the next utterance in a given dialogue. You will be given a few sentences describing the personality of the person who is making the dialogue, and a history of the dialogue after that. Each line in the history is said by one of the two participants in the conversation.
Ex Input:
Personality: I... | Must be nice in the summer I love summer, its the best season.
| 1 | NIv2 | task1729_personachat_generate_next | fs_opt | [
-0.6358141899108887,
0.05842093378305435,
-0.39386746287345886,
-0.17572252452373505,
-0.26845890283584595,
0.32322412729263306,
0.39839959144592285,
0.8287705779075623,
-0.4204980731010437,
0.03324213996529579,
-0.2589555084705353,
0.5213254690170288,
-0.2231571078300476,
-0.3080913424491... |
In this task, you need to count the number of words in a sentence that end with the given letter. Answer with numbers and not words.
[EX Q]: Sentence: 'a man sitting in front of a laptop computer'. How many words end with the letter 'r' in the sentence.
[EX A]: 1
[EX Q]: Sentence: 'teddy bear in front of a holly cove... | 1
| 6 | NIv2 | task163_count_words_ending_with_letter | fs_opt | [
-0.16964048147201538,
0.6409142017364502,
-0.1914699524641037,
-0.21708634495735168,
-0.09822310507297516,
0.34897342324256897,
-0.17157870531082153,
0.5711934566497803,
0.6329171657562256,
-0.18633434176445007,
-0.3432348370552063,
-0.25373780727386475,
-0.49018144607543945,
0.03198394551... |
In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a stereotype or ant... | Solution: Unrelated | 5 | NIv2 | task279_stereoset_classification_stereotype | fs_opt | [
0.04506809636950493,
0.44912973046302795,
-0.47863900661468506,
0.25566670298576355,
-0.14639762043952942,
-0.3023621141910553,
0.45650988817214966,
0.8757674694061279,
0.4098389148712158,
-0.7446988821029663,
-0.726504385471344,
0.18919818103313446,
-0.7491933107376099,
-0.287659674882888... |
Detailed Instructions: In this task, you're given a context passage, a question, and three answer options. Your task is to return an incorrect answer option to the question from the choices given. For all questions, only one of the three answer options is correct. Pick one of the two incorrect answer options as the out... | A | 8 | NIv2 | task385_socialiqa_incorrect_answer_generation | zs_opt | [
-0.6299238204956055,
0.0015810290351510048,
-0.5154907703399658,
-0.20890438556671143,
-0.3929376006126404,
-0.36246809363365173,
0.5685938596725464,
0.8971612453460693,
0.11271995306015015,
0.7779890298843384,
-0.8410535454750061,
-0.14574047923088074,
0.5693244338035583,
-0.4113249778747... |
Given a question and a context passage, generate the answer having the word or phrase from the context passage. Here, the answer should be a shortest continous span from the passage.
One example: Context: Architecturally, the school has a Catholic character. Atop the Main Building's gold dome is a golden statue of the ... | households | 6 | NIv2 | task469_mrqa_answer_generation | fs_opt | [
0.38617175817489624,
1.1121835708618164,
-0.49099451303482056,
0.1718551218509674,
0.1590844690799713,
-0.5861507654190063,
0.24685490131378174,
0.23332688212394714,
-0.12704233825206757,
0.17950034141540527,
0.04563230276107788,
0.49561384320259094,
0.18384917080402374,
-0.103197321295738... |
In this task, answer 'Yes' if the frequency of the given word in the two sentences is equal, else answer 'No'.
--------
Question: Sentence1: 'two men boogie boarding on a wave', Sentence2: 'these donuts have a lot of frosting on them'. Is the frequency of the word 'on' in two sentences equal?
Answer: Yes
Question: S... | No
| 7 | NIv2 | task159_check_frequency_of_words_in_sentence_pair | fs_opt | [
-0.2581433355808258,
0.4855940639972687,
-0.23721855878829956,
0.24991345405578613,
0.118556447327137,
-0.7074395418167114,
0.725919246673584,
0.805681049823761,
-0.5265419483184814,
-0.3613422214984894,
-0.5026511549949646,
-0.0060692280530929565,
-0.24584192037582397,
-0.0316293202340602... |
In this task, you are given triplets. Each triplet is in the form of [subject, predicate, object]. Your task is to generate proper sentence that utilizes these triples. The objective is to construct a sentence that (a) captures the facts specified in the triples and (b) is a well-formed sentence easily understandable b... | Been Around the World from No Way Out peaked at the top of the US Rap chart and 7th on the US R&B chart. | 9 | NIv2 | task1409_dart_text_generation | fs_opt | [
-0.36666139960289,
0.39921844005584717,
-0.6695200204849243,
-0.22795337438583374,
-0.005642046220600605,
-0.13071653246879578,
0.3474019765853882,
0.9116159677505493,
-0.24216940999031067,
0.14522111415863037,
-0.7366417646408081,
-0.12422378361225128,
-0.10479596257209778,
-0.48161968588... |
In this task, you are given a sentence in the Spanish language. Your task is to convert it to Lithuanian language.
Example: La dosis de mantenimiento es de 15 mg una vez al día, pero algunos pacientes pueden requerir dosis mayores.
Example solution: Palaikomoji dozė – 15 mg kartą per parą, nors kai kuriems pacientams g... | Solution: Tinkamai sunaikinkite nesuvartotą tirpalą. | 5 | NIv2 | task763_emea_es_lt_translation | fs_opt | [
0.042720481753349304,
0.6894193887710571,
-0.4070665240287781,
-0.3073269724845886,
-0.6732134222984314,
-0.8423067331314087,
1.664896011352539,
0.556450605392456,
0.2971978187561035,
-0.8610345721244812,
-0.4282362163066864,
0.7623554468154907,
-0.8367212414741516,
0.6302114725112915,
0... |
Given a post that is a real-life anecdote of a complex ethical situation and an associated claim about its type, verify if the claim is true or not. The claim asks if the posts are historical or hypothetical. The posts are "HISTORICAL" when the author has already done something and they are "HYPOTHETICAL" when the auth... | yes | 8 | NIv2 | task501_scruples_anecdotes_post_type_verification | fs_opt | [
0.2828640937805176,
0.1976093351840973,
0.0229264497756958,
0.03430626541376114,
-0.18298554420471191,
-0.06161295622587204,
0.5207016468048096,
1.4513084888458252,
-0.587766706943512,
-0.3698691725730896,
-0.07658800482749939,
0.04853792488574982,
-0.07601529359817505,
-0.1586526185274124... |
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.
[EX Q]: ਪ੍ਰਧਾਨ ਮੰਤਰੀ ਏਨੌਰ ਐੱਲਐੱਨਜੀ ਟਰਮੀਨਲ ਰਾਸ਼ਟਰ ਨੂੰ ਸਮਰਪਿਤ ਕਰਨਗੇ ।
[EX A]: પ્રધાનમંત્રી દેશને એન્નોર એલએનજી ટર્મિનલ અર્પણ કરશે.
[EX Q]: ਫਿਨਟੈੱਕ ਫਰਮਾ... | 56 એકર જમીન પ્રદાન કરવા સંમત થઈ છે, જે ભોપાલ એરપોર્ટની હાલની જમીનને લગોલગ છે અને એનો ઉપયોગ એએઆઈ દ્વારા ઉડ્ડયનનાં ઉદ્દેશો માટે થઈ શકશે.
| 6 | NIv2 | task1044_pib_translation_punjabi_gujarati | fs_opt | [
-0.3703387379646301,
-0.10258934646844864,
0.49723079800605774,
-0.6282442808151245,
-0.2460126280784607,
-0.9575886726379395,
0.10788562893867493,
0.3148640990257263,
-0.3467036485671997,
0.17378515005111694,
-0.6155022382736206,
0.2336060106754303,
-0.4080559313297272,
0.0827750861644744... |
Detailed Instructions: In this task, you're given a text and question. The question is about the topic of the document. You are expected to generate an incorrect answer. The incorrect answer should be among one of the following categories: 1)Company, 2)Educational Institution, 3)Artist, 4)Athlete, 5)Office holder, 6)Me... | Company | 8 | NIv2 | task631_dbpedia_14_incorrect_answer_generation | zs_opt | [
-0.19107306003570557,
0.5533504486083984,
-0.25941002368927,
0.8986414670944214,
0.24371570348739624,
-0.013104643672704697,
-0.6458961963653564,
0.2723836302757263,
0.04281109571456909,
0.10065954178571701,
-0.3239876329898834,
0.24997283518314362,
-0.2125827968120575,
-0.1399072110652923... |
In this task, you're given a context passage, 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 to a specific phrase from the paragraph. If multiple answers seem to exist, write the answer that is the most plausible.
... | write the articles
****
| 4 | NIv2 | task595_mocha_answer_generation | fs_opt | [
-0.19357600808143616,
0.922417163848877,
0.5343867540359497,
-0.15346360206604004,
-0.26961779594421387,
-0.13483275473117828,
0.7804785966873169,
0.3798651099205017,
-0.3619028329849243,
-0.357390820980072,
-0.4844323992729187,
0.06881575286388397,
-0.5416757464408875,
0.02071216888725757... |
In this task, you will be shown a prompt from a judicial decision and multiple holding statements derived from citations following text in a legal decision. Holdings represent the governing legal rule when the law is applied to a particular set of facts. There are five answer choices for each citing text. The correct ... | recognizing differing elements and standard of proof between medical malpractice and fraud
| 3 | NIv2 | task287_casehold_legal_incorrect_answer_generation | fs_opt | [
0.4377909302711487,
0.12794268131256104,
-0.11310704052448273,
-0.13103653490543365,
0.3445839583873749,
-0.4986700713634491,
0.5186474323272705,
1.2468938827514648,
-0.8606247901916504,
0.10449407249689102,
-0.5152479410171509,
0.07545275241136551,
-0.6371080279350281,
0.25813961029052734... |
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to... | No
| 6 | NIv2 | task1198_atomic_classification_owant | fs_opt | [
-0.034945227205753326,
0.09199362993240356,
0.08528256416320801,
-0.09525245428085327,
-0.7111430168151855,
-1.4113787412643433,
1.483200192451477,
0.23943763971328735,
-0.7147527933120728,
-0.4709773063659668,
-0.4201796054840088,
-0.25397253036499023,
-0.6869240999221802,
0.2104043960571... |
Given a sentence, generate a most likely context or previous statement. The previous statement should be relevant to the given statement.
[EX Q]: Several people are seen hitting the puck with one another with one panning around other shots and leads into him playing the game.
[EX A]: A few kids are seen standing on a ... | Behind her, someone combs her hair, her eyes fixed on the blonde.
| 6 | NIv2 | task455_swag_context_generation | fs_opt | [
0.16271835565567017,
0.6908800005912781,
-1.564139723777771,
-0.10226959735155106,
-0.7211498618125916,
-0.5878958702087402,
0.17765820026397705,
0.27333441376686096,
0.4320019483566284,
-0.43794557452201843,
0.17429929971694946,
0.6381555795669556,
-0.6001033782958984,
0.2333255410194397,... |
instruction:
In this task, you will be given a food review and a question about the reviewer's sentiment toward one aspect of the food in Persian. You have to infer the answer to the question from the review and classify it. Classify the reviewer's sentiment into: "no sentiment expressed", "negative", "neutral", "posit... | positive
| 9 | NIv2 | task524_parsinlu_food_aspect_classification | fs_opt | [
-0.9104138612747192,
-0.24595403671264648,
-0.38024041056632996,
0.2191559076309204,
-0.036536961793899536,
-0.12647530436515808,
1.1255347728729248,
0.8729618787765503,
0.3733903765678406,
0.1196584552526474,
-0.0001253979280591011,
-0.09527932107448578,
-0.6698768734931946,
0.07438818365... |
You will be given a passage, and your task is to generate a Yes/No question that is answerable based on the given passage.
Input: Consider Input: On September 17, 2008, the British evening-news analysis program Newsnight reported that Morgan Stanley was facing difficulties after a 42% slide in its share price. CEO Joh... | Output: is porto rico a part of the united states?
| 2 | NIv2 | task381_boolq_question_generation | fs_opt | [
0.0408237986266613,
0.16619685292243958,
-0.12955866754055023,
0.07423554360866547,
-0.3843276798725128,
0.6033406257629395,
0.35143470764160156,
0.889124870300293,
0.3335980176925659,
0.40750694274902344,
-0.20579341053962708,
0.9618259072303772,
-0.8233360052108765,
-0.21248789131641388,... |
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 commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "ye... | yes | 0 | NIv2 | task211_logic2text_classification | fs_opt | [
-0.1865157186985016,
-0.09893183410167694,
-0.17846029996871948,
0.5106772780418396,
0.428533673286438,
-0.45287805795669556,
0.041053496301174164,
0.6373380422592163,
0.07697625458240509,
0.013362353667616844,
-0.4419201910495758,
0.5246661901473999,
0.03203484043478966,
0.596934676170349... |
Given the task definition, example input & output, solve the new input case.
The given sentence contains a typo which could be one of the following four types: (1) swapped letters of a word e.g. 'niec' is a typo of the word 'nice'. (2) missing letter in a word e.g. 'nic' is a typo of the word 'nice'. (3) extra letter i... | stakc | 1 | NIv2 | task088_identify_typo_verification | fs_opt | [
-0.6630197763442993,
0.6842555999755859,
0.24455565214157104,
0.7148939967155457,
0.46909889578819275,
-0.31311267614364624,
0.030329301953315735,
0.873238205909729,
-0.2896539568901062,
0.4565562903881073,
-0.08653870224952698,
-0.3944466710090637,
-0.498820960521698,
-0.504206120967865,
... |
Part 1. Definition
In this task your given two statements. You must judge whether the second sentence is the cause or effect of the first one. Label the instances as "cause" or "effect" based on your judgment. The sentences are separated by a newline character.
Part 2. Example
The women met for coffee.
They wanted to c... | cause | 7 | NIv2 | task828_copa_commonsense_cause_effect | fs_opt | [
-0.05474218726158142,
0.47742635011672974,
-0.052342869341373444,
-0.6052864789962769,
-0.14965175092220306,
0.34732890129089355,
0.3762791156768799,
0.46499767899513245,
0.858843207359314,
-0.7039693593978882,
-0.381706178188324,
-0.4051830768585205,
-0.7790493965148926,
-0.09994657337665... |
Definition: 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.
Input: ['21', '413', 'e', '15', 'm', '291']
Output: | 1, 2, 3, 4, 5, 9 | 2 | NIv2 | task637_extract_and_sort_unique_digits_in_a_list | zs_opt | [
0.017853204160928726,
-0.21247224509716034,
-0.7420556545257568,
-0.2882797122001648,
0.0025441437028348446,
-0.1127258837223053,
0.5940924882888794,
-0.19296392798423767,
-0.3402104675769806,
0.21161440014839172,
-0.8853643536567688,
-0.07794750481843948,
-0.8626075983047485,
-0.503778696... |
Detailed Instructions: In this task, you are given a text from tweets. Your task is to classify given tweet text into two categories: 1) positive, and 2) negative based on its content.
Q: bridal shower today!!
A: | positive | 9 | NIv2 | task195_sentiment140_classification | zs_opt | [
-1.3859808444976807,
0.9181956052780151,
0.7432969808578491,
0.21842196583747864,
0.26312172412872314,
-0.5523229837417603,
-0.3990849256515503,
0.7097099423408508,
0.35456714034080505,
0.6045238971710205,
-0.2178289294242859,
-0.12391219288110733,
0.1206001341342926,
-0.6833499073982239,
... |
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.
Q: Ang S at P 500 na indise ay natapos sa 756.55 isang 6 na puntos at ang NASDAQ komposit ay may 5.40 na punto ang natamo pati na rin sa pagtatapo... | S&P500指数は6ポイント上げて756.55で終わり、ナスダック総合指数も同様に5.40ポイントあげて1431.50でその日を終えた。 | 4 | NIv2 | task1119_alt_fil_ja_translation | zs_opt | [
-0.240095317363739,
0.04162624105811119,
-0.09235215932130814,
-0.007356978952884674,
0.1774561107158661,
-0.4862496852874756,
0.5465672016143799,
0.08806242793798447,
-0.042346805334091187,
0.33401769399642944,
0.09717625379562378,
0.4168878197669983,
-0.3134235739707947,
0.68032944202423... |
Detailed Instructions: 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".
Problem:Paragraph: To report the... | True | 8 | NIv2 | task1162_coda19_title_classification | zs_opt | [
0.823745846748352,
0.027584634721279144,
-0.4262627363204956,
0.1991744041442871,
0.5829340815544128,
-0.39705324172973633,
0.6877829432487488,
0.5530866980552673,
-0.005086670629680157,
0.7798157930374146,
-0.3437609374523163,
0.5898717641830444,
-0.45892107486724854,
0.014265080913901329... |
Definition: 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).
Input: At least 80% of those suffering from the disease have s... | 病気を患っている人々の少なくとも80%は、他の薬剤に対する耐性を示した。 | 2 | NIv2 | task435_alt_en_ja_translation | zs_opt | [
-0.06755144894123077,
0.05321982502937317,
0.07315874844789505,
-0.8510053753852844,
0.31167417764663696,
0.027446314692497253,
0.5641250610351562,
0.7349416017532349,
0.3033823072910309,
-0.4005346894264221,
-0.7439741492271423,
0.5364718437194824,
-0.5875678062438965,
0.5999428033828735,... |
Given the task definition and input, reply with output. Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. ... | walk twice and look | 5 | NIv2 | task129_scan_long_text_generation_action_command_short | zs_opt | [
-0.003596317721530795,
0.7282077074050903,
-0.47402963042259216,
0.26414474844932556,
-0.21381735801696777,
0.34589964151382446,
0.21710240840911865,
0.25176215171813965,
-0.23592528700828552,
-0.17320790886878967,
-0.6780791282653809,
-0.3646159768104553,
-0.512311577796936,
0.05143876373... |
Teacher: You are given a sentence in Italian. Your job is to translate the Italian sentence into Polish.
Teacher: Now, understand the problem? If you are still confused, see the following example:
(Risate) E infatti aveva già pubblicato tanti video sulla natura.
Solution: (Śmiech) Opublikował wiele filmów o przyrodzie.... | Odpowiedź brzmi: nie, nie i jeszcze raz nie! | 2 | NIv2 | task1253_ted_translation_it_pl | fs_opt | [
-0.7647238969802856,
0.6307345032691956,
0.2603606581687927,
-0.36270028352737427,
-0.5891963243484497,
-0.4413985013961792,
0.1820679008960724,
0.4220593571662903,
-0.4632655382156372,
-0.37447160482406616,
-0.0020759941544383764,
0.2603263854980469,
-0.6982135772705078,
-0.20400199294090... |
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.
['t', 'c', '2941', 's', '6159']
t, c, s
['2401', 'h', '4909']
h
['i', 'Y', '6733', '6809', 'F', 'n', '7725', 't', '324... | i, Y, F, n, t, b, A, a, r, o
| 0 | NIv2 | task488_extract_all_alphabetical_elements_from_list_in_order | fs_opt | [
0.3177303969860077,
0.6551804542541504,
-0.656699538230896,
0.39818912744522095,
0.005204052664339542,
-0.6765881776809692,
0.10887575149536133,
-0.34091609716415405,
0.012270175851881504,
0.1713317632675171,
-0.6754686832427979,
0.0035587232559919357,
-0.1420690268278122,
0.05573419481515... |
Detailed Instructions: In this task, you are given a question and an answer, you would be asked to create the sentence based on the Question-Answer provided. It should be contained within the Question-Answer provided.
Q: Question: Prokaryotes are unicellular organisms that lack organelles surrounded by what? Answer: me... | Prokaryotes are unicellular organisms that lack organelles surrounded by membranes. | 9 | NIv2 | task1556_scitail_passage_generation | zs_opt | [
0.43763574957847595,
1.6638619899749756,
-0.1577722281217575,
-0.7470138072967529,
-0.3517836034297943,
-0.7952947020530701,
0.2954776883125305,
0.11305496096611023,
-0.23074427247047424,
-0.32693183422088623,
-0.20670099556446075,
-0.5730410814285278,
-0.40504226088523865,
-0.009551404975... |
Given the task definition and input, reply with output. In this task you are given a list of numbers and you need to find the average of each two consecutive values. The average of two numbers a and b is calculated as: (a + b) /2. The output should be a list of the averages of each two consecutive values. A list is pre... | [6.0, -35.5, -47.5, -48.5, -68.0, -51.0, -26.5, -39.5] | 5 | NIv2 | task124_conala_pair_averages | zs_opt | [
-0.8234602212905884,
0.4590744376182556,
-0.7307820916175842,
-0.2277947962284088,
-0.07995009422302246,
0.40927359461784363,
0.30437302589416504,
0.3651736080646515,
0.08917833119630814,
-0.37805894017219543,
-0.7381618022918701,
0.013718795962631702,
-0.13972200453281403,
0.4012495875358... |
Detailed Instructions: You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Q: Why was the stamp act the most hated taxes of the colonies ?
What did aristotle have right ?
What ca... | Why was the stamp act the most hated taxes of the colonies ? | 9 | NIv2 | task674_google_wellformed_query_sentence_generation | zs_opt | [
-0.33902639150619507,
0.06424462795257568,
0.02023344300687313,
-0.29210981726646423,
-0.08371909707784653,
-0.43136996030807495,
-0.02372869849205017,
0.233644500374794,
0.0983813926577568,
0.3772456645965576,
-0.25933951139450073,
-0.4668615460395813,
-0.9495394229888916,
-0.026251275092... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Portugese.
لو إنتظرنا حتى تحدث النوبة القلبية ، لضحينا بـ 1.1 مليون شخص كل عام في هذا البلد بسبب مرض القلب.
Output: | Se esperássemos até ao ataque cardíaco, estaríamos a sacrificar 1,1 milhões de vidas todos os anos neste país devido à doença cardíaca. | 1 | NIv2 | task1109_ted_translation_ar_pt | zs_opt | [
-0.4079403281211853,
0.5752605199813843,
0.19987232983112335,
-0.532849907875061,
-0.3364298641681671,
-0.3006872236728668,
0.25486791133880615,
0.677047610282898,
0.2672269940376282,
0.2036101520061493,
-0.610968828201294,
-0.5023120045661926,
-0.5062505006790161,
0.549044132232666,
1.4... |
In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Q: Fact1: Most ecosystems get energy from sunlight., Fact2: An ecosystem includes the organisms and their habitat., Question: what gets energy from sunlight? ... | A | 4 | NIv2 | task1297_qasc_question_answering | zs_opt | [
0.6615021228790283,
0.5654982328414917,
-0.5451751351356506,
-0.159857377409935,
-1.1132266521453857,
-1.5877223014831543,
-0.14327245950698853,
0.6927815675735474,
-0.32710132002830505,
-0.3917691111564636,
-0.3550904095172882,
-0.3197368383407593,
-0.6400086879730225,
-0.4083165526390075... |
Given a scientific question and its correct answer, generate supporting facts for the answer. This supporting fact can be an explanation for the answer to the given question.
One example is below.
Q: Question: What term refers to a list of the elements that will replace the ones below them in single-replacement reactio... | Stress is the force applied to a rock. There are four types of stresses:. | 9 | NIv2 | task593_sciq_explanation_generation | fs_opt | [
1.160093903541565,
0.039707034826278687,
-0.7733149528503418,
-0.14824840426445007,
0.05009179562330246,
-1.2906873226165771,
0.4123525023460388,
0.6775838732719421,
0.046180322766304016,
-0.4530383348464966,
-0.776961088180542,
-0.16237035393714905,
-0.7022179365158081,
-0.178377747535705... |
Instructions: In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Input: Fact1: carbon dioxide concentrations in the air have increased over the last decade dramatically, Fact2: Carbon dioxide is the primary gr... | H | 3 | NIv2 | task1297_qasc_question_answering | zs_opt | [
0.184892937541008,
0.45245128870010376,
-0.06232009455561638,
-0.4736116826534271,
-0.7641187906265259,
-1.0349806547164917,
-0.24180856347084045,
0.6562881469726562,
-0.07050509750843048,
0.21896082162857056,
-0.9148881435394287,
-0.628002941608429,
-0.3403128385543823,
-0.235214889049530... |
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.
Let me give you an example: Category: HOMOPHONIC PAIRS
Clue: It's a notation on a percussion ... | robert kerrey | 8 | NIv2 | task307_jeopardy_answer_generation_final | fs_opt | [
-0.8498331308364868,
0.726931095123291,
-0.7954256534576416,
0.04469083249568939,
0.5102379322052002,
-0.6387149095535278,
0.5176678895950317,
0.2112882137298584,
0.6200310587882996,
0.2082524597644806,
-0.13003921508789062,
0.32623228430747986,
-0.2743762135505676,
-0.24164149165153503,
... |
Teacher:"Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line of thought or context ("and..."). Given a prompt and two responses, identify which response is the type of "yes, and". Ind... | Response 1 | 6 | NIv2 | task362_spolin_yesand_prompt_response_sub_classification | zs_opt | [
0.26902854442596436,
0.5497133731842041,
0.5446127653121948,
-0.22574873268604279,
0.2359885275363922,
-0.8705501556396484,
0.13358233869075775,
0.7691367864608765,
-0.12319467961788177,
-0.6981586217880249,
-0.5520415306091309,
0.06739605963230133,
-0.7206593751907349,
0.05632884800434112... |
Teacher: Given a premise, an initial context, an original ending, and a counterfactual context, the task is to generate a new story ending aligned with the counterfactual context and as close to the original ending as possible. Each instance consists of a five-sentence story. The premise is the first sentence of a stor... | Jan's dad called his daughter downstairs so she could help. The girl agreed and helped. The girl, both plain and homely, looked after the store. | 2 | NIv2 | task269_csrg_counterfactual_story_generation | fs_opt | [
0.2754298448562622,
0.07566862553358078,
0.17625464498996735,
0.16189035773277283,
0.3471181392669678,
-0.6233404874801636,
0.06942011415958405,
1.300214171409607,
-0.009108269587159157,
-0.0016139697981998324,
-0.5067530274391174,
-0.025307580828666687,
-0.11075795441865921,
0.04719768837... |
Given the task definition and input, reply with output. In this task, you will be presented with a question having multiple possible answers in Japanese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Question: バラの花は何色が一般的ですか？
Options: A ... | A | 5 | NIv2 | task1145_xcsr_jap_commonsense_mc_classification | zs_opt | [
-0.3194769620895386,
0.4060700237751007,
0.14274540543556213,
0.09231158345937729,
-0.3046906888484955,
-0.2527120113372803,
0.35436543822288513,
0.4009099006652832,
0.26787787675857544,
-0.504746675491333,
-0.6144988536834717,
0.591582179069519,
0.05638974905014038,
0.24405115842819214,
... |
Given a sentence, generate a most likely context or previous statement. The previous statement should be relevant to the given statement.
[EX Q]: The camera turns around while still looking at the porch.
[EX A]: The camera walks to the end of the porch.
[EX Q]: Someone struggles to his feet and circles around someone... | There's a man standing in the hot sun on an extremely hot day with very high temperatures, showing how he can bake cookies in the open without using an oven.
| 6 | NIv2 | task455_swag_context_generation | fs_opt | [
-0.9211431741714478,
1.0642285346984863,
-0.16746152937412262,
0.22484803199768066,
-0.4423679709434509,
-0.3024097681045532,
-0.2444491684436798,
0.41788583993911743,
0.17553406953811646,
0.06441158056259155,
-0.06911332905292511,
0.2752189040184021,
-0.5915842652320862,
0.361011654138565... |
Q: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Arabic.
אם נביט היטב על נהר קונגו נמצאת אחת מהנקודות הזוהרות הללו. וזהו נהר הקונגו שמייצר אור - הלב החשוך לשעבר מייצר כיום אור בעזרת כוח הידרו אלקטרי
A: | لو نظر أحد بحذر ، في نهر الكنغو هو أحد تلك الأضواء المشعة ، وهذا النهر الكونغولي تحديداً يولد الضوء — القلب القديم للظلام — الآن يوليد الضوء بالطاقة الكهرومائية. | 7 | NIv2 | task1237_ted_translation_he_ar | zs_opt | [
-0.3581443130970001,
0.1633644998073578,
0.0531480573117733,
-1.317475438117981,
-0.8502843379974365,
-0.7886102199554443,
0.7282936573028564,
-0.16764113306999207,
0.16705283522605896,
-0.7744344472885132,
0.12716034054756165,
-0.6616257429122925,
-1.039354681968689,
0.09490782022476196,
... |
In this task, you're given a review from Amazon. Your task is to generate a rating for the product on a scale of 1-5 based on the review. The rating means 1: extremely poor, 2: poor, 3: neutral, 4: good, 5: extremely good.
Example Input: Love the shirt! My only complaint is that I wish the arms were a bit longer. I sh... | 3
| 3 | NIv2 | task1310_amazonreview_rating_classification | fs_opt | [
0.14095202088356018,
0.03968495875597,
-0.4010491967201233,
0.0595092736184597,
0.5058708190917969,
-0.20367056131362915,
0.3586859405040741,
0.7855082154273987,
-0.14615195989608765,
0.5993220210075378,
-0.0821661576628685,
0.33900120854377747,
-0.4074164927005768,
-0.4875403046607971,
... |
Teacher: 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 ... | No | 2 | NIv2 | task1214_atomic_classification_xwant | fs_opt | [
0.36619675159454346,
-0.054490890353918076,
0.458116352558136,
-0.23233522474765778,
-0.54952472448349,
-0.6032495498657227,
0.9242234230041504,
0.5444579720497131,
-0.4885231852531433,
-0.48334020376205444,
-0.1436758190393448,
-0.46441173553466797,
-0.847288966178894,
0.18627962470054626... |
Q: Given a sentence, generate a new sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
After... | After a marriage the humans want to bear along home . | 7 | NIv2 | task413_mickey_en_sentence_perturbation_generation | zs_opt | [
-0.10006178915500641,
0.9818698167800903,
-0.48132312297821045,
-0.3373967111110687,
0.04228903725743294,
-1.195948839187622,
0.9064817428588867,
0.5807163715362549,
0.38188350200653076,
-0.3609055280685425,
-0.6604397296905518,
0.2291724681854248,
-1.0997483730316162,
0.02921784110367298,... |
Given a sentence, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. Answer should be yes or no. Note that URLs in the text have been replaced with [Link].
One example: Verify if the sentiment of the following document towards the entity Bill Clinton is Negative. B... | yes | 6 | NIv2 | task422_persent_sentence_sentiment_verification | fs_opt | [
-1.538896083831787,
-0.2934103012084961,
0.755079984664917,
0.10848923772573471,
0.11595623195171356,
-1.5298340320587158,
0.6505966186523438,
0.2537771463394165,
0.46851301193237305,
0.21642999351024628,
0.23702624440193176,
0.026341132819652557,
-0.18843097984790802,
-0.2168889343738556,... |
In this task you will be given a passage and a yes/no question based on the passage. You should answer the question using the information from the passage.
[Q]: passage: This is a record of Canada's results at the FIFA World Cup. Canada has appeared in the FIFA World Cup on one occasion, which was in 1986.
question: ... | Yes
| 5 | NIv2 | task380_boolq_yes_no_question | fs_opt | [
-0.32428860664367676,
0.13807126879692078,
-0.6607030630111694,
0.21498140692710876,
-0.08740789443254471,
-0.3409656286239624,
0.6640318036079407,
0.7801283001899719,
0.36166250705718994,
0.07837126404047012,
-0.7634768486022949,
0.4026525020599365,
-0.09149861335754395,
-0.11178015172481... |
In this task, you are given a multiple-choice question and you have to pick the correct option. Answer with option indexes (i.e., "A", "B", "C", and "D").
Example input: Deserts are in extremely dry environments, so liquids will naturally be (A) rainbow (B) plentiful (C) meager (D) talented
Example output: C
Example e... | A | 3 | NIv2 | task1286_openbookqa_question_answering | fs_opt | [
-0.5526394844055176,
0.20968985557556152,
0.18743672966957092,
-0.27419137954711914,
-0.6194560527801514,
-0.9738693237304688,
0.44981998205184937,
0.8081357479095459,
-0.15314097702503204,
-0.007684255018830299,
-0.5533589124679565,
-0.16090041399002075,
0.2841465175151825,
-0.56078314781... |
You will be given a definition of a task first, then some input of the task.
You are given an amazon food product review and its polarity (positive or negative). Your task is to answer "True" if the specified sentence and its polarity match; otherwise, answer "False".
This sauce is an excellent blend of sweet and spic... | False | 1 | NIv2 | task587_amazonfood_polarity_correction_classification | zs_opt | [
-0.4120367169380188,
-0.4799290895462036,
0.5150392055511475,
-0.0866490975022316,
-0.039498016238212585,
-0.06986037641763687,
1.1404951810836792,
0.31573203206062317,
0.20103541016578674,
0.1640215367078781,
-0.45804503560066223,
0.07484839856624603,
-0.37105393409729004,
-0.412438839673... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence or phrase in English. You must translate it to Xhosa in a way that is equivalent in terms of meaning and grammatically correct.
Telescopes of new contrivance with Six Glasses and Telescopes for Day and N... | Izahlulo zesine zezangqa zikaGunter noluhlu oluqinileyo, zonke iintlobo zegilasi zohambo, enye, okanye ezimbini nezine zeyure | 1 | NIv2 | task872_opus_xhosanavy_translation_eng_xhosa | zs_opt | [
-0.1069144532084465,
0.4812231659889221,
0.41020792722702026,
-0.20487122237682343,
-0.10662676393985748,
-0.11403200030326843,
0.7688150405883789,
0.2557561993598938,
0.20771534740924835,
-0.5977163910865784,
-0.27880799770355225,
0.06800656765699387,
-0.2764497697353363,
-0.2381098270416... |
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