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 |
|---|---|---|---|---|---|---|
Detailed Instructions: 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.
Problem:Had issues with first unit, customer service was great in getting ... | 4 | 8 | NIv2 | task1310_amazonreview_rating_classification | zs_opt | [
-0.13442501425743103,
-0.40920424461364746,
-0.18227902054786682,
-0.09660869091749191,
0.29051709175109863,
-0.11022721976041794,
0.931080162525177,
0.8824607729911804,
-0.2632976472377777,
0.8498059511184692,
-0.8123294711112976,
-0.24238428473472595,
-0.5713413953781128,
0.1894997358322... |
Definition: In this task, we ask you to rewrite a sentence in simple English without changing its general meaning. Essentially, you want to make the sentence easier to read by using simpler words, utilizing more straightforward sentence structures, and omitting non-essential information etc.
Input: A timer which counts... | A timer which counts upwards from zero for measuring time is often called a " stopwatch " . | 2 | NIv2 | task933_wiki_auto_style_transfer | zs_opt | [
-0.4897788166999817,
0.569901704788208,
-0.11693143844604492,
0.1754332035779953,
0.07206093519926071,
-0.29326921701431274,
0.5345864295959473,
0.16236554086208344,
0.4494270384311676,
0.3041560649871826,
-0.6021652221679688,
-0.022996647283434868,
-0.559242844581604,
0.32647374272346497,... |
Detailed Instructions: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_). The sentence pair should look similar and should be about two different persons (PersonX and PersonY). Additionally, the two sentences must be different in terms of trigger word... | Sentence 1: Emptying the litter box was a dreaded chore for PersonX while PersonY didn't mind doing it. _ always tried to get someone else to handle it.
Sentence 2: Emptying the litter box was a dreaded chore for PersonX while PersonY didn't mind doing it. _ never tried to get someone else to handle it. | 8 | NIv2 | task030_winogrande_full_person | zs_opt | [
0.10968339443206787,
0.5146286487579346,
-0.06438888609409332,
-0.18528422713279724,
0.2906368374824524,
-0.3338678479194641,
0.8985305428504944,
0.7320139408111572,
0.009264362044632435,
-0.4276770353317261,
-0.38627707958221436,
-0.05158533155918121,
-0.545819878578186,
0.178148448467254... |
Given a sentence, generate a most unlikely next statement. The next statement should not be logically relevant to the given context
Ex Input:
He walks slowly away along the deserted platform, as the train gathers speed. High on a hill beyond the station, Hogwarts School
Ex Output:
squats down to earnest eyes at the b... | applies the picture to the boy.
| 1 | NIv2 | task454_swag_incorrect_answer_generation | fs_opt | [
0.2301521897315979,
0.9355074167251587,
-0.5666842460632324,
-1.0966713428497314,
0.12573130428791046,
-0.5928184986114502,
-0.00781485065817833,
0.01172126829624176,
-0.21950094401836395,
-0.3668942153453827,
-0.12399055063724518,
-0.01995737850666046,
-0.09712781012058258,
-0.50288516283... |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write an implausible POS tag to the question. Even though there exist multiple wrong answers, we only need a single wrong answer. Here is the Alphabetical list of part-of-speech tags used in this task: CC... | DT
| 6 | NIv2 | task347_hybridqa_incorrect_answer_generation | fs_opt | [
0.43730583786964417,
0.5600706338882446,
-0.34033676981925964,
-0.039812956005334854,
0.25932806730270386,
-0.18538013100624084,
0.6902027130126953,
1.1135215759277344,
-0.6421933770179749,
0.04188167303800583,
-0.521966814994812,
0.7521538734436035,
-0.45670583844184875,
0.201574787497520... |
Instructions: The input is a tweet which can be classified as Hate Speech, Offensive or Normal. Given such a tweet, output the class the tweet belongs to. Hate Speech will contain threatening language towards the community targeted. Offensive language will contain abusive or discriminatory language towards the communit... | Offensive | 3 | NIv2 | task1502_hatexplain_classification | zs_opt | [
-0.798614501953125,
0.6578191518783569,
0.215205579996109,
0.7695401906967163,
-0.5462689995765686,
-0.6066923141479492,
-0.028377549722790718,
0.4194034934043884,
0.8299540281295776,
-0.10640682280063629,
-0.314815878868103,
-0.08608448505401611,
-0.08027010411024094,
-0.6616251468658447,... |
In this task you will be given an arithmetic operation and you have to find its answer. The symbols of operators '+' and '-' has been swapped i.e you need to perform subtraction when you see a '+' symbol and addition in case of '-' symbol.
Ex Input:
1989 - 7828 - 4806 - 7481 + 9860 - 9696 - 7086 + 272 + 8952
Ex Outp... | 6945
| 1 | NIv2 | task085_unnatural_addsub_arithmetic | fs_opt | [
-0.6888096332550049,
0.1901017725467682,
-1.199070692062378,
0.14651502668857574,
-0.30155426263809204,
0.10736791789531708,
0.44304871559143066,
1.2106572389602661,
0.39566683769226074,
-0.5039709806442261,
-0.5721679925918579,
-0.15562403202056885,
-0.5305188894271851,
-0.050970897078514... |
You are given a sentence and a question in the input. If the information provided in the sentence is enough to answer the question, label "Yes", otherwise label "No". Do not use any facts other than those provided in the sentence while labeling "Yes" or "No". There are only two types of valid responses: Yes and No.
Se... | Yes. | 0 | NIv2 | task050_multirc_answerability | zs_opt | [
-0.5619966983795166,
0.6574001312255859,
0.30985066294670105,
0.586284339427948,
-0.3749195635318756,
-1.2222049236297607,
0.25755321979522705,
0.7870211601257324,
-0.15042203664779663,
-0.023548800498247147,
-0.12794643640518188,
0.1103609949350357,
-0.17515811324119568,
-0.09354259073734... |
Given a command in a limited form of natural language, provide the correct sequence of actions that executes the command to thus navigate an agent in its environment. A command can be broken down into many different actions. Actions are uppercase and are individual steps that serve as the building blocks for a command.... | I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_RIGHT I_RUN I_TURN_LEFT I_RUN I_TURN_LEFT I_RUN I_TURN_LEFT I_RUN I_TURN_LEFT I_RUN I_TURN_LEFT I_RUN I_... | 5 | NIv2 | task130_scan_structured_text_generation_command_action_long | fs_opt | [
0.4141351580619812,
0.5585465431213379,
-0.5208366513252258,
0.30988529324531555,
-0.09167879819869995,
-0.2912902235984802,
0.05833931267261505,
0.36002880334854126,
-0.24081572890281677,
-0.17225617170333862,
-0.8393433094024658,
0.050076164305210114,
-0.4293173551559448,
-0.153321057558... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given reviews from Amazon, classify those review based on their content into two classes: Negative or Positive.
I've read this book with much expectation, it was very boring all through out the book... | Positive | 0 | NIv2 | task493_review_polarity_classification | fs_opt | [
-0.4308764934539795,
-0.4023962616920471,
0.3745756149291992,
-0.9878522157669067,
0.9034614562988281,
0.1978742480278015,
1.1087589263916016,
0.011260081082582474,
0.22587618231773376,
0.4572378993034363,
-0.2321721613407135,
-0.41203057765960693,
-0.7737330794334412,
-0.2790159583091736,... |
Given the task definition and input, reply with output. You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Japanese.
Nos anos oitenta, conforme a América passou pela transição do período Reagan, entre a economia manufatureira do meio-oeste parao Vale do Silício na Califórnia,... | 1980年代レーガン政権時代にアメリカが経験した転換つまり中西部の製造業基盤の経済からカリフォルニアのシリコンバレー経済への転換は「アメリカの終焉」と言われました | 5 | NIv2 | task1275_ted_translation_pt_ja | zs_opt | [
-0.2152629792690277,
0.3858097195625305,
-0.06721936166286469,
-0.4103437066078186,
-0.5624708533287048,
0.05700337514281273,
-0.19744953513145447,
0.7703192234039307,
0.29545724391937256,
-0.28761178255081177,
-0.19248422980308533,
-0.1635408103466034,
0.04828878864645958,
0.1198304742574... |
In this task, you are given Twitter posts. Your task is to label the post's emotion (as expressed by the user) as sadness, joy, love, anger, fear, or surprise.
Example input: im feeling quite sad and sorry for myself but ill snap out of it soon
Example output: sadness
Example explanation: The emotion of the post is sa... | surprise | 3 | NIv2 | task512_twitter_emotion_classification | fs_opt | [
-0.7580974102020264,
-0.21580104529857635,
0.3075612783432007,
0.4899239242076874,
0.1963106095790863,
-0.4315755367279053,
0.10432152450084686,
0.40936118364334106,
0.20032574236392975,
0.15222866833209991,
0.13372544944286346,
-0.042222943156957626,
-0.5265616774559021,
0.050309017300605... |
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: Problem: on a sum of money , the simple interest for 2 years is rs . 330 , while the compound interest is rs . 340 , the rat... | Solution: e | 5 | NIv2 | task1419_mathqa_gain | fs_opt | [
0.9882721900939941,
0.09060706198215485,
-0.5982711911201477,
-0.03048943541944027,
0.03508775308728218,
-0.8619499206542969,
1.3733432292938232,
0.9650951027870178,
-0.06312976777553558,
0.11612755060195923,
-0.5916456580162048,
0.24094395339488983,
-0.963909387588501,
-0.3295717835426330... |
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Farsi.
One example is below.
Q: 私たちはただひたすら歌い続けましたすると驚くことに信頼が芽生え友情が花開いたのです
A: ما آواز خوندیم ، و خوندیم ، آواز خونديم ، و بطور شگفت انگیزی اعتماد جدید رشد کرد ، و درواقع دوستی شکوفه زد.
Rationale: The Japanese sentence is correctly... | چیزی که ما در گاندو داریم کوزه های گِلی هستند. | 9 | NIv2 | task1098_ted_translation_ja_fa | fs_opt | [
0.6523059606552124,
1.0599331855773926,
-0.14726057648658752,
-0.05359776318073273,
-0.4353751242160797,
-0.8399873971939087,
1.2944495677947998,
0.1228485032916069,
0.0782155692577362,
-0.2720349133014679,
-0.7552475333213806,
0.275570809841156,
-1.0054925680160522,
0.6532883644104004,
... |
In this task, you will be presented with a question having multiple possible answers in Vietnamese language. And you should choose a most suitable option out of "A", "B", "C", "D", and "E" based on your commonsense knowledge.
Input: Consider Input: Question: Ong dành thời gian đi du lịch ở đâu?
Options: A trên cánh ... | Output: A
| 2 | NIv2 | task1130_xcsr_vi_commonsense_mc_classification | fs_opt | [
-0.3454527258872986,
0.3541197180747986,
-0.23194432258605957,
0.0033445912413299084,
-0.41170865297317505,
-0.8978919982910156,
0.0899471640586853,
1.2407622337341309,
-0.10662631690502167,
0.058904942125082016,
0.1800549030303955,
0.2018033266067505,
0.35968151688575745,
-0.2203957140445... |
Definition: In this task, you're given the title of a five-sentence story, the first four sentences, and two options for the fifth sentence as a and b. Your job is to pick the sentence option that does not connect with the rest of the story, indicating your choice as 'a' or 'b'. If both sentences are plausible, pick th... | b | 2 | NIv2 | task214_rocstories_incorrect_ending_classification | zs_opt | [
-0.32805800437927246,
-0.30270272493362427,
0.4867148995399475,
-0.2865002453327179,
-0.21176669001579285,
0.7148492932319641,
0.008161809295415878,
0.8579598665237427,
0.5633621215820312,
0.02540213242173195,
-0.8925796151161194,
-0.22121313214302063,
0.4137395918369293,
-0.32751306891441... |
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 | 6 | NIv2 | task935_defeasible_nli_atomic_classification | fs_opt | [
0.23885469138622284,
0.21531859040260315,
-0.8198589086532593,
-0.16069766879081726,
-0.2867608666419983,
-1.1682732105255127,
1.1117216348648071,
1.060023546218872,
0.45703935623168945,
-0.7136332988739014,
-1.222412109375,
-0.1901833415031433,
-0.9205981492996216,
-0.12225690484046936,
... |
The given sentence contains a typo which could be one of the following four types: (1) swapped letters of a word e.g. 'niec' is a typo of the word 'nice'. (2) missing letter in a word e.g. 'nic' is a typo of the word 'nice'. (3) extra letter in a word e.g. 'nicce' is a typo of the word 'nice'. (4) replaced letter in a ... | mna | 4 | NIv2 | task088_identify_typo_verification | zs_opt | [
-0.9897388815879822,
0.4224291741847992,
-0.07461929321289062,
0.24968349933624268,
0.09099668264389038,
-1.0409443378448486,
1.0772371292114258,
-0.16868856549263,
0.3040301203727722,
0.03131534531712532,
-0.2385319173336029,
-0.37431785464286804,
-0.8892816305160522,
0.05407318100333214,... |
This task is in Spanish. Based on the given context, generate a question which can be answered by the given context. Generate a question that has more than 7 words. You can paraphrase the given context while forming the question.
Suggestion: The question may involve starting question words like WHERE, WHEN, HOW, WHAT ... | ¿En qué evento musical actuará la banda francesa?
| 0 | NIv2 | task1335_sqac_question_generation | fs_opt | [
0.19082055985927582,
0.06396026164293289,
-0.4135294556617737,
-0.43900924921035767,
0.7172271609306335,
-0.04195065051317215,
0.631483256816864,
0.7339560389518738,
-0.6641207933425903,
0.1498810052871704,
-0.15798747539520264,
0.6333986520767212,
-0.48927041888237,
0.041868969798088074,
... |
Teacher:You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Arabic.
Teacher: Now, understand the problem? Solve this instance: Portanto, eu queria ser professora.
Student: | لذا أردت أن تصبح معلمة. | 6 | NIv2 | task1277_ted_translation_pt_ar | zs_opt | [
-0.419084370136261,
0.41982901096343994,
0.07098618149757385,
-1.2757030725479126,
-0.45413270592689514,
0.20143964886665344,
0.15637388825416565,
0.25485706329345703,
0.9444588422775269,
-0.1046251505613327,
-0.17127938568592072,
-0.19486099481582642,
-0.5012035369873047,
-0.7991653680801... |
You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Japanese.
Q: ¿Y saben qué?
A: | 一方こちらの「ネコ動画映画際」に対しては | 4 | NIv2 | task1227_ted_translation_es_ja | zs_opt | [
-0.23411135375499725,
0.8127375245094299,
-0.12838071584701538,
-0.5115220546722412,
0.4181719422340393,
-0.640956699848175,
-0.02817533165216446,
0.07237493991851807,
0.8416615724563599,
-0.43250975012779236,
-0.39912381768226624,
-0.03250352293252945,
-0.7546350955963135,
0.3887650370597... |
Given an English language product review, determine if it is a Good Review or a Bad Review. A good review is one where the product's review has positive tone and Bad review is one where the tone of product's review is negative.
Q: This seat lounge chair has two advantages.
A: | Good Review | 4 | NIv2 | task929_products_reviews_classification | zs_opt | [
-0.8915790319442749,
0.761898398399353,
-0.5621104836463928,
0.2981886863708496,
-0.3008682131767273,
-0.25025230646133423,
0.23486600816249847,
0.7917479276657104,
0.9439945220947266,
0.48427215218544006,
0.6712292432785034,
0.079967200756073,
-0.6580350399017334,
0.5083701610565186,
-0... |
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 Spanish.
Są obecnie wystarczająco małych rozmiarów, żeby zmieścić się na biurku.
Output: | Las hay tan pequeñas que caben en un escritorio. | 1 | NIv2 | task1258_ted_translation_pl_es | zs_opt | [
-0.7385289669036865,
1.3442180156707764,
-0.4852544665336609,
-0.13923081755638123,
-0.028823591768741608,
-0.029167696833610535,
0.5572421550750732,
0.2285466343164444,
0.8726309537887573,
-0.4819025993347168,
-0.02293255738914013,
0.6142505407333374,
0.08546355366706848,
-0.1635598540306... |
In this task, you are given an input list. A list contains several comma-separated items written within brackets. You need to return the position of all the alphabetical elements in the given list in order. Assume the position of the 1st element to be 1. Return -1 if no alphabetical element is in the list.
Let me give... | 2, 5, 6, 7, 10, 13, 16, 18, 19, 24, 28, 30, 31, 32, 33, 34, 37, 39, 40 | 8 | NIv2 | task506_position_of_all_alphabetical_elements_in_list | fs_opt | [
-0.19347988069057465,
0.1541764736175537,
-0.1710180938243866,
-0.48916828632354736,
0.2928749620914459,
-0.388133704662323,
0.48157820105552673,
0.354094922542572,
-0.5840402245521545,
0.10757732391357422,
-0.7269265651702881,
-0.21285954117774963,
0.13703009486198425,
-0.0447703301906585... |
You are given a sentence in Persian. Your job is to translate the Farsi sentence into Polish.
Let me give you an example: ایلان: درسته. این مهمه که بخش های راکت بتونند برگردند و بتونند به سایت پرتاب برگردند و اماده پرتاب باشند در عرض چند ساعت.
The answer to this example can be: EM: Owszem. Ważne jest by rakieta mogła ... | Jak wiesz, są dwie części... EP: Wiesz jak to nazywam? | 8 | NIv2 | task1272_ted_translation_fa_pl | fs_opt | [
-0.5786897540092468,
0.977814793586731,
0.5117162466049194,
0.23325768113136292,
-0.6832932233810425,
-0.02081712894141674,
1.412492275238037,
-0.044055547565221786,
0.16120974719524384,
-0.6472431421279907,
-1.206165075302124,
1.136110782623291,
-1.1167775392532349,
0.5564970970153809,
... |
You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Japanese.
Q: والذي قرروا هم عدم فعل ذلك
A: | 検察は彼を再び訴追することなく | 4 | NIv2 | task1231_ted_translation_ar_ja | zs_opt | [
-0.9037400484085083,
0.7901877164840698,
0.009893053211271763,
-0.7699528932571411,
-0.5274242758750916,
0.5812076330184937,
0.5011134743690491,
0.20189331471920013,
1.044628381729126,
-0.8315954208374023,
-0.06043677031993866,
-0.036022402346134186,
-0.6064882278442383,
-0.086570680141448... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Hebrew.
Então, o que é que temos que fazer para resolver este problema?
Output: | אז מה אנחנו צריכים לעשות כדי לפתור את הבעיה? | 1 | NIv2 | task1278_ted_translation_pt_he | zs_opt | [
-0.3625842332839966,
1.1384241580963135,
0.1664825677871704,
-0.1306353360414505,
-0.3189549446105957,
0.7507729530334473,
0.32326066493988037,
0.23917406797409058,
1.2157641649246216,
0.0795118659734726,
-0.6374980211257935,
-0.014823230914771557,
-0.5828943252563477,
-0.1195736974477768,... |
You will be given a definition of a task first, then some input 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 replaced by generic words (e.g., PersonX, Pers... | No | 1 | NIv2 | task1204_atomic_classification_hinderedby | zs_opt | [
0.7532802820205688,
0.31334152817726135,
0.49843546748161316,
-0.12992048263549805,
-0.22523286938667297,
-0.9012175798416138,
0.9846290946006775,
0.22553716599941254,
-0.5150667428970337,
-0.3379878103733063,
-0.4632313847541809,
-0.666082501411438,
-0.5562926530838013,
0.3256593942642212... |
instruction:
In this task, you're given reviews from Amazon's products. Your task is to generate the Summary of the review.
question:
Rollers(wheels) don’t really roll on hard surfaces, rather end up dragging around long clean and unlock ineffectual! If weren’t so heavy to ship back, I would have!
answer:
Rollers(wheel... | Person needing it passed away and the company would not ...
| 9 | NIv2 | task618_amazonreview_summary_text_generation | fs_opt | [
-0.23805147409439087,
0.4268452823162079,
-0.4522794485092163,
-0.03472863882780075,
-0.1217050850391388,
-0.11360126733779907,
0.30120933055877686,
0.5241035223007202,
-0.02111382782459259,
0.03921008110046387,
0.20328585803508759,
0.7334258556365967,
-0.338643878698349,
0.417632460594177... |
Detailed Instructions: In this task, you need to count the number of nouns/verbs in the given sentence.
Q: Sentence: 'A black cat sitting in front of a banana'. Count the number of verbs in this sentence.
A: | 1 | 9 | NIv2 | task155_count_nouns_verbs | zs_opt | [
0.32998186349868774,
0.8824551701545715,
-0.4659881591796875,
-0.34366559982299805,
-0.5986039638519287,
0.09898988902568817,
0.12245345860719681,
0.4081094264984131,
-0.00610882043838501,
0.1493453085422516,
0.057168297469615936,
-0.10751902312040329,
-0.5686586499214172,
0.27666565775871... |
Detailed Instructions: In this task your given two statements in Vietnamese. 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.
Q: Cặp đôi đã đính hôn.
Họ lên kế hoạch ... | effect | 9 | NIv2 | task1183_xcopa_commonsense_cause_effect_vi | zs_opt | [
-0.41365736722946167,
0.39786049723625183,
-0.2310968041419983,
-0.34913843870162964,
-0.2326086163520813,
-0.3699601888656616,
0.26616668701171875,
1.5363175868988037,
0.5437633991241455,
-0.10639233142137527,
-0.27146783471107483,
0.36030465364456177,
-0.45323288440704346,
0.151310682296... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a paragraph, a question, and a candidate incorrect answer to the question. Your goal is to judge whether the provided answer is a valid incorrect answer to a given question. An incorrect answer should not truthfully... | Yes. | 1 | NIv2 | task057_multirc_classify_incorrect_answer | zs_opt | [
0.524630069732666,
0.23429173231124878,
-0.40410116314888,
0.31943708658218384,
0.49462270736694336,
-0.1278478503227234,
0.8145131468772888,
0.43000900745391846,
0.16972970962524414,
0.1397857964038849,
-0.5835820436477661,
0.06621553748846054,
-0.7640091180801392,
0.25654101371765137,
... |
instruction:
In this task, you are given one english sentence. The major part of the sentences talk about health-related topics, but some of the them describe an organization and its activities. Your job is to translate the given sentences into German.
question:
The most frequent infections are urinary tract infections... | Die Tagungen sind in der Regel in Form von Plenarsitzungen und Workshops organisiert, was die Diskussion und die Konsensbildung über die Ergebnisse erleichtert.
| 9 | NIv2 | task1396_europa_ecdc_tm_en_de_translation | fs_opt | [
0.4708522856235504,
0.0936782956123352,
-0.4481646418571472,
-0.37277793884277344,
0.10921256989240646,
0.25880885124206543,
-0.13901060819625854,
-0.09414365142583847,
-0.14270585775375366,
0.0894838348031044,
0.5832300186157227,
0.22994615137577057,
-0.18222838640213013,
0.60282218456268... |
Given the task definition, example input & output, solve the new input case.
A text is given in Malayalam. Translate it from the Malayalam language to the Marathi language. The translation must not omit or add information to the original sentence.
Example: ഈ സംവിധാനത്തിന് പൊതു ടൈം-ടേബിളും പൊതു ടിക്കറ്റിംഗ് സംവിധാനവും ക... | अर्थात, हा पहिला सामना होता, त्यामुळं तो लक्षात राहणार, हे तर स्वाभाविकच आहे. | 1 | NIv2 | task1071_pib_translation_malayalam_marathi | fs_opt | [
0.7086663246154785,
0.48435211181640625,
-0.576270580291748,
0.19348490238189697,
0.7161862254142761,
-0.9072926044464111,
-0.05503632873296738,
0.4927337169647217,
-0.1320073902606964,
0.1649608016014099,
-0.6316720247268677,
-0.5324535369873047,
0.010787039995193481,
-0.10904629528522491... |
You are given a sentence in Persian. Your job is to translate the Farsi sentence into English.
Input: Consider Input: خب بیایید با برخی خبرهای خوب شروع کنیم ، و خبرهای خوب با چیزی سروکار دارد که ما بر مبنای تحقیقات بیوپزشکی می دانیم که به راستی یافته هارا برای شماربسیار زیادی از بیماریهای جدی تغییر داده است.
Output... | Output: And in that classic old-timey style of yesteryear, we're all going to watch something at the exact same time, together.
| 2 | NIv2 | task1265_ted_translation_fa_en | fs_opt | [
-0.6170593500137329,
0.5288338661193848,
-0.19240228831768036,
-0.3438495695590973,
-0.6889262199401855,
-0.4895208179950714,
0.557147741317749,
0.5182302594184875,
0.26338255405426025,
-0.23449501395225525,
-0.8427339196205139,
0.8247922658920288,
-0.2625829875469208,
0.3272976875305176,
... |
You will be given a context and a question in Spanish. Your job is to generate answers that are at least THREE words long.
The answers need to be context specific and can not be general knowledge or a random guess.
One example: CONTEXT: La historia de Japón (日本の歴史 o 日本史, Nihon no rekishi / Nihonshi?) es la sucesión de... | en la revista Naturalist's Miscellany | 6 | NIv2 | task1334_sqac_answer_generation | fs_opt | [
-0.15765488147735596,
-0.06567402184009552,
-0.03813408687710762,
0.4194776117801666,
0.013796054758131504,
-0.45199042558670044,
0.45515719056129456,
0.949216365814209,
0.020631734281778336,
-0.2139454185962677,
-0.2535809874534607,
1.0671807527542114,
-1.3903510570526123,
0.3034325540065... |
Instructions: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
Input: セルフコントロールは将来の問題ではありません
Output: | ضبط النفس ليس مشكلة في المستقبل. | 3 | NIv2 | task1224_ted_translation_ja_ar | zs_opt | [
-0.01289242971688509,
0.4226231276988983,
-0.04135936126112938,
-1.2026550769805908,
-0.9284024238586426,
0.43274185061454773,
0.26519501209259033,
0.47840219736099243,
0.7326870560646057,
-0.4181610345840454,
-0.7429561614990234,
-0.1346515715122223,
-0.045686349272727966,
0.0037242830730... |
Teacher: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.
Teacher: Now, understand the problem? Solve this instance: ['3251', 'K', '233', '2289', 'l', 's', '9439', '989', ... | K, l, s, o, B, L, H, i | 6 | NIv2 | task488_extract_all_alphabetical_elements_from_list_in_order | zs_opt | [
-0.5013794898986816,
0.7135847806930542,
-0.29647380113601685,
-0.43003126978874207,
-0.42336317896842957,
-0.4521220326423645,
0.31730854511260986,
-0.04129966348409653,
-0.3210221529006958,
0.24541731178760529,
-0.28247252106666565,
-0.3749043643474579,
0.5108296871185303,
-0.19987277686... |
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".
Input: Paragraph: Newton's Principia intr... | False | 3 | NIv2 | task1162_coda19_title_classification | zs_opt | [
-0.4012739658355713,
1.0347590446472168,
-0.2921910881996155,
-0.4845653772354126,
-0.5431728363037109,
-0.5161055326461792,
0.49186620116233826,
0.2214346081018448,
0.27921152114868164,
0.006692271213978529,
-0.7329314947128296,
0.2502840757369995,
-0.6626149415969849,
-0.5719058513641357... |
In this task, you are given a sentence in the English language and your task is to convert it into the Swedish language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
The Portuguese Presidency has agreed to initiate deliberations on this mat... | Rådets portugisiska ordförandeskap har sagt ja till att arrangera överläggningar om detta, för att möjligen få en utvidgning av mandatet. | 0 | NIv2 | task313_europarl_en_sv_translation | zs_opt | [
0.012648912146687508,
0.7510198950767517,
0.5071946978569031,
-0.7487045526504517,
0.19019830226898193,
-0.3122056722640991,
0.9071573615074158,
0.5516995787620544,
0.5246529579162598,
0.16612006723880768,
-0.41370251774787903,
0.20082169771194458,
-0.43723660707473755,
-0.0177304502576589... |
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 need to count the number of words in a sentence that start with the given letter. Answer with numbers and not words.
Sentence: 'a hot dog in a bun with ketchup on a plate with fren... | 2 | 0 | NIv2 | task162_count_words_starting_with_letter | fs_opt | [
0.1916406750679016,
0.06522510945796967,
-0.2639352083206177,
-0.45313528180122375,
-0.37514352798461914,
-0.16068699955940247,
0.2983749508857727,
0.30369582772254944,
0.5451391339302063,
-0.8687502145767212,
-0.19281622767448425,
0.11754105985164642,
-0.06432804465293884,
0.0877218097448... |
You will be given a definition of a task first, then some input of the task.
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 ans... | N | 1 | NIv2 | task190_snli_classification | zs_opt | [
-0.2618633508682251,
0.41677379608154297,
-0.6865009665489197,
-0.16545921564102173,
-0.10181175917387009,
-0.10268408060073853,
0.12682130932807922,
0.42187750339508057,
0.844365119934082,
-0.12992128729820251,
-0.6411072015762329,
-0.28600388765335083,
0.3759326934814453,
-0.230794772505... |
Given the task definition and input, reply with output. In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ).... | Yes | 5 | NIv2 | task1198_atomic_classification_owant | zs_opt | [
0.02674218639731407,
0.40607327222824097,
0.3559081554412842,
0.01996682584285736,
-0.29317617416381836,
-0.5604573488235474,
1.3071218729019165,
0.27031463384628296,
-0.4026624262332916,
-0.5413773655891418,
-0.3891550898551941,
-0.2972549498081207,
-0.7665921449661255,
0.2263491153717041... |
In this task you are given a sentence. You must judge whether the object of the main clause is singular(like: apple) or plural(like: apartments). Label the instances as "Singular" or "Plural" based on your judgment.
I held the pages over a powerful light bulb, and up to the sunlight, but I could find nothing. | Plural | 0 | NIv2 | task431_senteval_object_count | zs_opt | [
-1.124537467956543,
1.0500906705856323,
0.10586930811405182,
-0.22586402297019958,
-0.5845483541488647,
-0.4324301779270172,
0.9544788599014282,
0.35871413350105286,
-0.012946180999279022,
-0.6405911445617676,
-0.30684322118759155,
0.14628610014915466,
-0.5754793286323547,
-0.5124561786651... |
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 the individual's beli... | green_basket | 0 | NIv2 | task153_tomqa_find_location_hard_clean | zs_opt | [
0.09942154586315155,
-0.11630618572235107,
-0.13151833415031433,
-0.6528202891349792,
-0.5871602296829224,
-0.32475805282592773,
0.4960190951824188,
0.9904622435569763,
0.317768394947052,
-0.12809154391288757,
-0.39279279112815857,
0.45955750346183777,
0.2585645318031311,
0.109790325164794... |
Teacher: In this task, you are given a set of context paragraphs, some supporting facts and an answer of a question. Your task is to generate question for given answer based on set of context paragraphs, supporting facts and an answer.
Teacher: Now, understand the problem? If you are still confused, see the following e... | Which building was build for the Minnesota National Guard in 19351936, that began to host the Minneapolis Lakers in 1959? | 2 | NIv2 | task191_hotpotqa_question_generation | fs_opt | [
0.781674325466156,
0.3039230704307556,
-0.9326530694961548,
0.9370003938674927,
0.4748004078865051,
-0.2512519061565399,
0.5479238033294678,
0.4632471203804016,
-0.20790012180805206,
0.4270770847797394,
0.08803431689739227,
0.49254661798477173,
-0.8295868635177612,
-0.2549578547477722,
0... |
Given the task definition, example input & output, solve the new input case.
Generate an appropriate title for the given text. The generated title must be short and include the main topic of the text. The preferred titles are under fifteen words.
Example: But Eluned Morgan conceded that it would be "difficult for us to... | Black Lives Matter: Bletchley councillor's protest tweets investigated | 1 | NIv2 | task1356_xlsum_title_generation | fs_opt | [
-0.038502536714076996,
1.056321620941162,
0.5421794652938843,
-0.38395535945892334,
0.8061881065368652,
-0.01122969575226307,
0.2101731151342392,
0.7876120805740356,
-0.6698271036148071,
0.3626019358634949,
0.20588962733745575,
0.41422849893569946,
-0.01048684399574995,
0.17763552069664001... |
Teacher:In this task, you are given a review of movie. Your task is to classify given movie review into two categories: 1) positive, and 2) negative based on its content.
Teacher: Now, understand the problem? Solve this instance: Nicolas Roeg ? He directed the classic supernatural thriller DON`T LOOK NOW didn`t he ? St... | negative | 6 | NIv2 | task284_imdb_classification | zs_opt | [
-0.37765198945999146,
0.2768937349319458,
-0.09347860515117645,
0.11275329440832138,
0.260651171207428,
0.02333328127861023,
0.9197896718978882,
1.0194485187530518,
-0.02791711874306202,
0.3134203553199768,
-0.2801849842071533,
-0.038490213453769684,
-0.676116943359375,
-0.1338093578815460... |
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
One example: It 's a lovely film with lovely performances by Buy and Accorsi .
Solution is here: POS
Explanation: Th... | NEG | 6 | NIv2 | task363_sst2_polarity_classification | fs_opt | [
-0.8685199618339539,
0.5658906698226929,
0.18317601084709167,
-0.00934753380715847,
0.1304607391357422,
-0.6441456079483032,
0.7781544923782349,
0.34320417046546936,
0.10346334427595139,
0.2249656319618225,
-0.6603027582168579,
-0.4235052466392517,
0.5884093046188354,
0.2618367373943329,
... |
You are given a sentence in Persian. Your job is to translate the Farsi sentence into Portugese.
--------
Question: یک خطای نوع اول ، یا مثبت نادرست ، باور به وجود داشتن یک الگو است وقتی که وجود ندارد.
Answer: O erro Tipo I, ou falso positivo, é acreditar que o padrão é real quando não o é.
Question: تقریبا یک حرف د... | Tinha de ser governado em línguas diferentes.
| 7 | NIv2 | task1273_ted_translation_fa_pt | fs_opt | [
-0.8467214703559875,
-0.18112769722938538,
0.1499750316143036,
0.09813585877418518,
-0.02637392096221447,
0.39756157994270325,
1.0367166996002197,
0.3201051354408264,
0.27064597606658936,
-0.3378466069698334,
-1.1227296590805054,
-0.5986274480819702,
-0.7197244167327881,
0.0659654885530471... |
Given the task definition and input, reply with output. This task is to translate a news commentary given in French language into Russian language. Translate the input statement into the output language while preserving the numberical values, special characters and proper nouns and context of the commentary done.
Et à... | И так оно и должно быть: расширение НАТО - это не экспансия, представляющая угрозу для России или других стран, стремящихся к демократическим политическим реформам. | 5 | NIv2 | task1377_newscomm_translation | zs_opt | [
-0.6415287256240845,
0.6472815275192261,
-0.19466358423233032,
0.2902461588382721,
-0.3101387321949005,
0.3172491192817688,
0.6603304147720337,
0.45494234561920166,
0.49793511629104614,
-0.04089503735303879,
-0.7229132056236267,
-0.3883764147758484,
-0.396786630153656,
0.37540361285209656,... |
In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".
One example is below.
Q: Paragraph: The severe acute re... | False | 9 | NIv2 | task1162_coda19_title_classification | fs_opt | [
0.5272281765937805,
0.31114429235458374,
-0.39009231328964233,
0.42361387610435486,
0.5199064612388611,
0.13136839866638184,
0.6117467284202576,
0.8037793636322021,
-0.3495723009109497,
0.6290930509567261,
-0.24222484230995178,
0.8205211162567139,
0.2736550569534302,
0.2522558569908142,
... |
Detailed Instructions: 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'.
Q: Problem: two years ago , ram put $ 1000 into a savings account . at the end of the first year , his account... | e | 9 | NIv2 | task1419_mathqa_gain | zs_opt | [
0.4267996549606323,
0.721086859703064,
-0.07991524785757065,
-0.11775049567222595,
-0.6985632181167603,
-0.6337026953697205,
1.080941081047058,
1.0487468242645264,
0.13193278014659882,
0.08766153454780579,
-0.6382933855056763,
0.3675749599933624,
-1.3951692581176758,
-0.4290367066860199,
... |
Given the task definition and input, reply with output. Given a sentence, generate a most unlikely next statement. The next statement should not be logically relevant to the given context
He floats motionless with his eyes closed. She
| watches the departing fall flee, and finds someone's arm wrapped around her. | 5 | NIv2 | task454_swag_incorrect_answer_generation | zs_opt | [
0.20817816257476807,
1.138851523399353,
0.47329139709472656,
-0.5163804292678833,
0.0753508135676384,
0.676048755645752,
0.08114821463823318,
0.3892916738986969,
0.5102683305740356,
-0.22166486084461212,
-0.8430747389793396,
-0.25499576330184937,
-0.2742195129394531,
-0.32634469866752625,
... |
Detailed Instructions: In this task, you are given a text which is the body of a document. You are given a question and options. Pick the correct number. Don't generate anything else apart from the numbers provided in options.
Q: Context: SEGi University founded in 1977 as Systematic College is located in Kuala Lumpur.... | 2 | 9 | NIv2 | task633_dbpedia_14_answer_generation | zs_opt | [
-1.0351146459579468,
0.1039310097694397,
0.4861838221549988,
-0.4532981514930725,
0.07686648517847061,
-0.9549462795257568,
0.07941314578056335,
-0.14000916481018066,
-0.17620594799518585,
0.054467517882585526,
0.004061116836965084,
0.030305959284305573,
-0.059043753892183304,
0.6806350946... |
Detailed Instructions: 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'.
Q: They can smile.
A: | 1 | 9 | NIv2 | task1346_glue_cola_grammatical_correctness_classification | zs_opt | [
-0.586188554763794,
1.3054313659667969,
0.1618063896894455,
-0.9347138404846191,
0.39827030897140503,
-1.064591884613037,
0.25505703687667847,
0.6220846176147461,
0.3081728518009186,
-0.10443393886089325,
-0.4966353178024292,
-0.614507257938385,
0.5207049250602722,
-0.6582117676734924,
0... |
Definition: You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotio... | No emotion,happiness | 2 | NIv2 | task1532_daily_dialog_emotion_classification | zs_opt | [
-0.8285234570503235,
0.11546828597784042,
0.24375119805335999,
-0.37803980708122253,
0.11142420768737793,
-0.0956592783331871,
0.6662653088569641,
-0.8218175768852234,
0.06797658652067184,
-0.6001161336898804,
-0.06063847243785858,
-0.43464195728302,
-0.3442862629890442,
0.7089213132858276... |
Instructions: In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You ... | No | 3 | NIv2 | task1212_atomic_classification_hasproperty | zs_opt | [
0.3880329132080078,
0.3026449680328369,
0.31891733407974243,
-0.08972533792257309,
-0.6056318879127502,
-0.7399811148643494,
1.207497477531433,
0.6540805697441101,
-0.5252135396003723,
-0.26497983932495117,
-0.44952595233917236,
-0.49293744564056396,
-0.5540745258331299,
0.2749472558498382... |
Given the task definition and input, reply with output. You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Farsi.
Ele continuava a afirmar que, mesmo com a melhor educação, eu não iria receber um tratamento justo.
| دائم می گفت حتی با داشتن بهترین تحصیلات هم باز به حقوق برابر نمی رسی. | 5 | NIv2 | task1282_ted_translation_pt_fa | zs_opt | [
-0.550216794013977,
1.221277117729187,
0.6613599061965942,
-0.7004460096359253,
-0.286416620016098,
0.08303307741880417,
0.08108998835086823,
1.1946535110473633,
0.01646127551794052,
0.37465304136276245,
-0.060385651886463165,
0.47863590717315674,
-0.5375021696090698,
-0.198357954621315,
... |
Teacher:You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. You are required to assign a label 'formal' if there is an absence of emotion and a presence of questions anywhere within the conversation. If such pattern is not found assign the label 'i... | informal | 6 | NIv2 | task1533_daily_dialog_formal_classification | zs_opt | [
-0.32625967264175415,
0.3438808023929596,
0.39350831508636475,
-0.24248026311397552,
-0.04839897155761719,
0.12716826796531677,
0.38643428683280945,
0.2249438464641571,
-0.24737219512462616,
0.17841799557209015,
0.2398168444633484,
-0.5882905721664429,
-0.13481585681438446,
-0.030977863818... |
Part 1. Definition
In this task, you are given a statement spoken by a politician in natural language. Your task is to generate the subject of the discussion for the given statement. The subject generated is not necessarily a part of the given input. Your answer should contain one or more words.
Part 2. Example
Says th... | campaign-finance | 7 | NIv2 | task613_politifact_text_generation | fs_opt | [
0.42856138944625854,
0.11940721422433853,
-0.5279370546340942,
0.43036067485809326,
-0.24935537576675415,
-0.570702075958252,
0.41482940316200256,
-0.23346000909805298,
0.1761334240436554,
0.47858431935310364,
-0.02769254893064499,
0.17072437703609467,
-0.3213736414909363,
-0.2128673344850... |
TASK DEFINITION: Given a scientific question, generate an incorrect answer to the given question. The incorrect answer should be a plausible alternative to the correct answer. The answer should be some other item belonging to the same category as the correct answer but should be incorrect.
PROBLEM: What consists mainly... | at conduction
| 8 | NIv2 | task592_sciq_incorrect_answer_generation | fs_opt | [
0.42404794692993164,
0.8565205335617065,
-0.3979896605014801,
-0.4743203818798065,
-0.5948840379714966,
-0.11067330837249756,
0.42234736680984497,
0.455799400806427,
0.11559772491455078,
-0.47584956884384155,
-0.6706353425979614,
0.20627865195274353,
-0.8905943632125854,
0.3048925399780273... |
Detailed Instructions: This task is about identifying the subject of a given sentence. The subject of a sentence is the person, place, or thing that is performing the action of the sentence. The subject represents what or whom the sentence is about. Each sentence in this task is guaranteed to contain a single subject. ... | A.C. Lumezzane | 8 | NIv2 | task1411_dart_subject_identification | zs_opt | [
-0.26415014266967773,
1.1827917098999023,
-0.7162066102027893,
-0.31292271614074707,
-0.5227164030075073,
-0.5259536504745483,
0.967365026473999,
0.04125406593084335,
0.1185464859008789,
-0.4548003673553467,
-0.9971165060997009,
0.11732271313667297,
-0.6444160342216492,
0.316125750541687,
... |
Detailed Instructions: You will be given a person's personality, and a history of a conversation this person has had. You will be given four candidate sentences to complete the conversation, based on the context. Choose one and answer with the text.
Problem:Personality: My mom was a hairdresser.
My favorite color is re... | Whats your favorite color? Mine is red. | 8 | NIv2 | task1730_personachat_choose_next | zs_opt | [
-0.5281714200973511,
0.2134353369474411,
-0.18713980913162231,
-0.18904508650302887,
-0.5694077610969543,
0.5460874438285828,
0.45685112476348877,
0.5142307877540588,
0.06297019124031067,
0.1548495590686798,
-0.35498353838920593,
-0.6965526342391968,
0.35068637132644653,
-0.405336320400238... |
Detailed Instructions: You are given a sentence in Galician. Your job is to translate the Galician sentence into Farsi.
Q: Os respiradeiros hidrotérmicos descubríronse en 1977 no noso océano.
A: | حفره های آب گرم در اعماق اقیانوس های ما در سال ۱۹۷۷ کشف شدند. | 9 | NIv2 | task1245_ted_translation_gl_fa | zs_opt | [
-0.20857781171798706,
0.7132436037063599,
-0.5958445072174072,
-0.45585209131240845,
0.13196034729480743,
-0.7880086302757263,
0.40332677960395813,
-0.015010209754109383,
0.23701772093772888,
-0.07704862952232361,
-0.5140165686607361,
0.08508127927780151,
-0.9900437593460083,
0.21059429645... |
In this task, you are given a sentence which is either in the Swedish language or English language. You task is to identify the language of input sentence. Input sentence can be in Swedish or English language only and also it cannot have two languages at a time.
[Q]: Därutöver hänvisas det till nödvändigheten av ökad ... | English
| 5 | NIv2 | task315_europarl_sv-en_language_identification | fs_opt | [
-0.21576368808746338,
0.6870365142822266,
0.717114269733429,
-0.18233945965766907,
0.0420721098780632,
-0.17692670226097107,
0.6239028573036194,
0.4321853816509247,
0.6598502397537231,
-0.32477352023124695,
-0.08242461085319519,
0.5111318230628967,
-0.3689501881599426,
-0.5600599646568298,... |
Definition: In this task, you will be presented with a question in Dutch language, and you have to write the location names from the question if present. B denotes the first item of a phrase and an I any non-initial word. Identifier used for the location name - LOC. . There can be instances with no location name entity... | Libië: B-LOC | 2 | NIv2 | task1546_conll2002_location_name_extraction_answer_generation | zs_opt | [
-0.04384476691484451,
0.08926895260810852,
-0.13069021701812744,
0.08535348623991013,
-0.5525060892105103,
0.5828806161880493,
0.4589589238166809,
0.0343557670712471,
0.6062589883804321,
-0.46470528841018677,
-0.7302172780036926,
0.43854689598083496,
0.1486109495162964,
0.41150182485580444... |
Detailed Instructions: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
See one example below:
Problem: អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃពីធីប្រកួតពានរង្វាន់ពិភពលោកនៃកីឡាបាល់ឱបឆ... | うち数人は負傷の治療のため、その後病院へ搬送された。 | 4 | NIv2 | task1122_alt_khm_ja_translation | fs_opt | [
0.3140453100204468,
0.7728298306465149,
-0.7398321032524109,
0.09123389422893524,
-0.36167240142822266,
-0.7371116876602173,
0.4367813467979431,
0.36958906054496765,
0.05731580778956413,
-0.30015188455581665,
-0.6650193333625793,
0.7420706748962402,
-0.6143286228179932,
0.8116217851638794,... |
Q: You are given a text of the tweet and a corresponding label whether this tweet is 'Offensive', 'Hate Speech' or 'Neither'. Your job is to identify if the label is correct. Generate label 'true' if it's correct, 'false' otherwise.
Tweet: @michaeldbirch What else do you expect from that nigger lover?
Label: Hate Speec... | true | 7 | NIv2 | task905_hate_speech_offensive_classification | zs_opt | [
-1.4966115951538086,
0.6117873191833496,
0.4838724136352539,
0.11795389652252197,
-0.5910929441452026,
-1.063544511795044,
0.34703385829925537,
0.33179083466529846,
0.9094673991203308,
0.2341924011707306,
-0.13728070259094238,
-0.5424203872680664,
-1.0946646928787231,
-0.4958092272281647,
... |
Detailed Instructions: You are given a sentence in Polish. Your job is to translate the Polish sentence into Japanese.
See one example below:
Problem: Wszystko jest robione pomiędzy żebrami.
Solution: 全て肋骨の間から行うのです
Explanation: The Polish sentence is correctly translated into Japanese, because the meaning is preserved.... | 始めますよ | 4 | NIv2 | task1257_ted_translation_pl_ja | fs_opt | [
0.12627598643302917,
0.5242011547088623,
-0.3344925343990326,
0.4586802124977112,
0.07082109153270721,
-0.1819116175174713,
1.2285947799682617,
-0.6980425119400024,
-0.3663906455039978,
-0.3024110198020935,
-0.2466752678155899,
0.4818694591522217,
-0.6554132699966431,
0.8328697085380554,
... |
You are given a sentence in English. Your job is to translate the English sentence into Arabic.
Ex Input:
No one's noticed, have they yet?
Ex Output:
لن يلاحظ احد ذلك, هل لاحظ احد ذلك ؟
Ex Input:
We have a lot of interesting information about what complexity is.
Ex Output:
لدينا العديد من المعلومات الهامة حول مفهو... | بني في حي قاسي حيث ترك الناس ليموتوا.
| 1 | NIv2 | task1220_ted_translation_en_ar | fs_opt | [
-0.09619762748479843,
0.5776403546333313,
0.016544640064239502,
-0.46094438433647156,
0.07765959948301315,
-0.6390252709388733,
1.2607617378234863,
0.3284159004688263,
0.0005412537138909101,
-0.27197226881980896,
-0.7447007894515991,
0.2779284119606018,
-0.4695538878440857,
0.0493049323558... |
Detailed Instructions: You are given a sentence in Galician. Your job is to translate the Galician sentence into English.
Problem:E tamén, hai outras formas de activar a FOXO que nin sequera fan intervir á insulina ou IGF-1 iso podería ser aínda máis seguro.
Solution: | And also, there are other ways of activating FOXO that don't even involve insulin or IGF-1 that might even be safer. | 8 | NIv2 | task1238_ted_translation_gl_en | zs_opt | [
-0.20096158981323242,
0.4261544942855835,
0.24398687481880188,
-0.48779499530792236,
-0.12106381356716156,
-0.8898956179618835,
0.5156431794166565,
1.3165283203125,
-0.6315336227416992,
-0.16747348010540009,
-1.0370628833770752,
-0.5155989527702332,
-0.8484442830085754,
0.01682161167263984... |
In this task, you will be shown an extract from a movie plot. You need to read the extract and create questions that can be answered from the extract. The questions should be well-formed and grammatically correct. The questions should be completely answerable from the given passage and should not require any external k... | Output: What is kamratuppfostran?
| 2 | NIv2 | task193_duorc_question_generation | fs_opt | [
0.790112316608429,
0.18762671947479248,
-0.5826045274734497,
0.014501769095659256,
0.3695574700832367,
-0.06830716878175735,
0.9151486158370972,
0.36239051818847656,
-0.08014024794101715,
0.4697284698486328,
-0.0072303758934140205,
0.6277321577072144,
-0.23988258838653564,
0.18360073864459... |
Definition: Given a sentence in the Thai, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Input: ส่วนโมฮันติกล่าวว่าผู้เสียชีวิตร้อยละ 85 ตายในพายุหมุนสูงขึ้นไปจากพื้นดิน และว่าการพยากรณ์ขนาดและตำแหน่งการพุ่งสูงของพายุหมุนลักษณะ... | モハンティは、サイクロンによる死の８５パーセントが暴風による高潮によるもので、そのような高潮の大きさと位置の予測が災害予測で重要であると言う。 | 2 | NIv2 | task1128_alt_th_ja_translation | zs_opt | [
-0.5979050993919373,
-0.29108065366744995,
-0.1952289342880249,
-0.1982850432395935,
-0.42814603447914124,
-0.6246735453605652,
0.9493870735168457,
0.6150833964347839,
-0.10510370880365372,
-0.06987501680850983,
-1.2054353952407837,
0.22391077876091003,
-0.5997356176376343,
1.1683442592620... |
TASK DEFINITION: In this task, you will be shown a conversation. You need to write a question with three choices for the conversation. Your question should be answerable based on the conversation and only have one correct answer. Note that you don't need to answer your question. "W" and "M" in the conversations stand f... | What do you know about the pictures? (A) They were taken in France. (B) Kate is good at taking pictures. (C) They were taken by Sam.
| 8 | NIv2 | task246_dream_question_generation | fs_opt | [
0.5802738666534424,
0.046649135649204254,
-0.5900399684906006,
0.04666535556316376,
0.3929164409637451,
-0.25675612688064575,
1.5693821907043457,
0.5202198624610901,
-0.7583422660827637,
0.29437321424484253,
0.03426898643374443,
0.521685004234314,
-0.32905852794647217,
0.4584529399871826,
... |
In this task, you will be presented with a question in Dutch language, and you have to write the person names from the question if present. B denotes the first item of a phrase and an I any non-initial word. Phrase used for the person name - PER. There can be instances with no person name entity, then return 'None'.
I... | Output: Thierry: B-PER, Timmermans: I-PER
| 2 | NIv2 | task1545_conll2002_person_name_extraction_answer_generation | fs_opt | [
-0.5292767286300659,
0.9689943194389343,
0.09016171097755432,
0.10516424477100372,
0.01265425980091095,
-0.30651700496673584,
1.2124024629592896,
0.03711266815662384,
0.5967438220977783,
-0.21066740155220032,
-0.0756433978676796,
0.9055652022361755,
0.24060407280921936,
-0.1002704501152038... |
Instructions: In this task, you need to count the number of vowels (letters 'a', 'e', 'i', 'o', 'u') / consonants (all letters other than vowels) in the given sentence.
Input: Sentence: 'an old design kitchen with a long counter and brown appliances'. Count the number of vowels in the given sentence.
Output: | 18 | 3 | NIv2 | task157_count_vowels_and_consonants | zs_opt | [
0.43478646874427795,
0.8774779438972473,
-1.001206636428833,
-0.5054574012756348,
-0.06938941031694412,
0.03488884121179581,
-0.25502580404281616,
0.7841638922691345,
-0.23102548718452454,
-0.17009316384792328,
-0.3148977756500244,
-0.025980275124311447,
-0.09824950993061066,
-0.5633461475... |
This task involves creating questions from a given passage that involve some kind of complex reasoning (including numerical reasoning).
The generated questions must require looking at more than one part of the passage to answer. Try to use a variety of reasoning types in your questions (some of the sample reasoning ty... | How many field goals did Josh Brown make? | 0 | NIv2 | task026_drop_question_generation | zs_opt | [
0.6612983345985413,
0.22873687744140625,
-0.2385260909795761,
0.5285799503326416,
-0.13383080065250397,
-0.38794761896133423,
-0.003962662070989609,
0.19937363266944885,
-0.10400868952274323,
0.08316613733768463,
-0.7096883058547974,
0.0981529951095581,
-1.1425174474716187,
0.1920354217290... |
Read the given text and if it has abusive content then indicate via "yes". Otherwise indicate via"no".
We consider the content to be abusive if it contains any of the following instances: (1) Identity Directed Abuse (e.g., Content which contains a negative statement made against an identity. An identity is a social ca... | yes
****
| 4 | NIv2 | task108_contextualabusedetection_classification | fs_opt | [
-0.13722041249275208,
0.054801374673843384,
0.4010131359100342,
0.3079817295074463,
-0.19065450131893158,
-0.6320734024047852,
0.4146535396575928,
0.7050271034240723,
-0.029827134683728218,
0.617465078830719,
0.11556747555732727,
-0.412524551153183,
-0.30853167176246643,
-0.811734557151794... |
In this task, you are given two sets, and you need to count the number of elements 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 common to both ... | 2 | 4 | NIv2 | task243_count_elements_in_set_intersection | zs_opt | [
0.19221000373363495,
0.33734774589538574,
-0.9265340566635132,
-0.23401693999767303,
-0.14251019060611725,
0.03613254800438881,
0.6209601163864136,
0.35119181871414185,
-0.08113411068916321,
-0.07689197361469269,
-0.829032301902771,
0.2646302580833435,
0.1360751986503601,
0.034611612558364... |
Definition: In this task, you are given a sentence in the Bulgarian language and corresponding English translation of this sentence. Here, your job is to generate label "yes" if translation is right, otherwise generate label "no".
Input: Bulgarian: 16., English: Discharge 2005: European Agency for Safety and Health at ... | no | 2 | NIv2 | task273_europarl_classification | zs_opt | [
0.2449873983860016,
-0.04336400330066681,
0.2120044231414795,
0.5840753316879272,
0.27162933349609375,
-0.4200402498245239,
0.7449038624763489,
0.1707564890384674,
1.045637607574463,
0.24199679493904114,
-0.4921102225780487,
0.6461679339408875,
-0.523990273475647,
0.24053891003131866,
0.... |
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... | Alfonso: B-PER, Spa: B-LOC, F.: B-PER, de: I-PER, Boer: I-PER, Ned: B-LOC, Djorkaeff: B-PER, Fra: B-LOC, Inzaghi: B-PER, Ita: B-LOC, Mendieta: B-PER, Spa: B-LOC, Overmars: B-PER, Ned: B-LOC, Shearer: B-PER, Eng: B-LOC, Smicer: B-PER, Tsj: B-LOC, Sükür: B-PER, Tur: B-LOC, Totti: B-PER, Ita: B-LOC, Zenden: ... | 8 | NIv2 | task1544_conll2002_named_entity_recognition_answer_generation | fs_opt | [
0.4737948775291443,
0.10870858281850815,
-0.2182127833366394,
0.5173118114471436,
0.0392574667930603,
-0.13144537806510925,
0.27934351563453674,
-0.13005924224853516,
0.4774004817008972,
-0.6103013753890991,
-0.7647148370742798,
0.622298002243042,
-0.14586655795574188,
0.008033400401473045... |
Given the task definition, example input & output, solve the new input case.
In this task, we ask you to elaborate the sentence without changing its general meaning. You can do so by explaining further the input sentence, using more precise wording, adding qualifiers and auxiliary information etc.
Example: The Inherita... | The underlying cause of the ciliopathies may be a dysfunctional molecular mechanism in the primary cilia structures of the cell , organelles which are present in many cellular types throughout the human body . | 1 | NIv2 | task955_wiki_auto_style_transfer | fs_opt | [
-0.4092171788215637,
0.7011354565620422,
-0.5213876962661743,
0.05274203419685364,
-0.14785604178905487,
-0.5035860538482666,
0.5613226890563965,
0.49223756790161133,
-0.03825904056429863,
-0.48815974593162537,
-0.2511141896247864,
-0.15456518530845642,
-0.4050239026546478,
0.0080587780103... |
In this task, you are given Yelp reviews. The task is to classify a review as "POSITIVE" if the overall sentiment of the review is positive or as "NEGATIVE" if the overall sentiment of the review is negative.
One example is below.
Q: This is my go to place to get the best chicken Pad Thai! Also the price is super good,... | POSITIVE | 9 | NIv2 | task475_yelp_polarity_classification | fs_opt | [
-0.40282848477363586,
-0.2941131591796875,
-0.07847192883491516,
0.41906923055648804,
0.9007991552352905,
-0.23206770420074463,
0.8064677715301514,
1.1935195922851562,
-0.08506764471530914,
0.12480588257312775,
0.036469392478466034,
-0.006816058419644833,
-0.33624136447906494,
0.6096880435... |
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the q... | When did the player who scored the only and winning goal for Manchester United stop playing for them? | 9 | NIv2 | task235_iirc_question_from_subtext_answer_generation | fs_opt | [
0.31286686658859253,
0.3172987699508667,
-0.6921728253364563,
0.48254629969596863,
0.3373441696166992,
-0.5328507423400879,
0.6360652446746826,
0.9992530345916748,
0.15163537859916687,
-0.08335598558187485,
-0.3246310353279114,
0.4560587406158447,
-1.3664296865463257,
0.03982173651456833,
... |
In each example you will read a short sentence (or two). Then, a pronoun in the text is mentioned. Your task is to choose a referent which the mentioned pronoun refers to. You will be given two options in each case and one choice should seem much more likely to you than the other.
[Q]: sentence: kirk promised andy to ... | shatova
| 5 | NIv2 | task249_enhanced_wsc_pronoun_disambiguation | fs_opt | [
-0.30056464672088623,
0.5697178840637207,
0.544404923915863,
-0.32528144121170044,
-0.12612612545490265,
-0.28099995851516724,
0.8331378698348999,
0.09028448164463043,
0.6491859555244446,
-0.02680777944624424,
-0.11156949400901794,
0.051763713359832764,
-0.6617030501365662,
0.6629930734634... |
Q: 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... | Yes | 7 | NIv2 | task426_hindienglish_corpora_hi-en_classification | zs_opt | [
-0.5865075588226318,
0.3742162585258484,
0.6600788235664368,
0.14893940091133118,
-0.23318320512771606,
-0.5441756248474121,
0.2471558004617691,
0.7777992486953735,
-0.13155409693717957,
-0.4564821720123291,
-0.25701993703842163,
0.4356458783149719,
-0.5648869276046753,
-0.0182070434093475... |
You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into English.
Let me give you an example: Os astrónomos acreditam que cada estrela da galáxia tem um planeta, e especulam que até um quinto deles tem um planeta do tipo da Terra que poderá ter vida, mas ainda não vimos nenhum dele... | Now is the time to create something new, something vital. | 8 | NIv2 | task1274_ted_translation_pt_en | fs_opt | [
0.1442941427230835,
0.7754174470901489,
0.018154293298721313,
-0.3235873281955719,
-0.2131483554840088,
-0.7891910076141357,
-0.34778353571891785,
0.526403546333313,
0.5418289303779602,
-0.47012558579444885,
-0.16574282944202423,
0.6960923671722412,
-0.5397884845733643,
0.1864595115184784,... |
The task is about translation from Telugu to English. While performing the translation you must preserve the original meaning. Do not include any words which are only limited to your native place.
తిరిగి వ్యాపారంలో ఒక దేశం క్లబ్ జైలు, రెండు అవ్ట్, వద్ద ఆరు సంవత్సరాల. | Six years at a country club jail, out in two, back in business. | 0 | NIv2 | task1324_open_subtitles_te_en_translation | zs_opt | [
-0.4302380681037903,
1.091165542602539,
-0.016341200098395348,
0.7440547943115234,
0.34130334854125977,
-0.3638932406902313,
0.10872995853424072,
-0.22442087531089783,
-0.39724093675613403,
-0.5073941946029663,
-0.5742761492729187,
0.6108152866363525,
-1.2006208896636963,
0.397264391183853... |
Teacher: 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).
Teacher: Now, understand the problem? If you are still confused,... | -LRB- ii -RRB- Second Reading : Second Reading forms the most elaborate and vital stage in the life of a Bill because it is at this stage that it receives detailed and minute examination . | 2 | NIv2 | task424_hindienglish_corpora_hi_en_translation | fs_opt | [
0.12145839631557465,
-0.047003041952848434,
0.7634196281433105,
-0.016726495698094368,
0.3413694500923157,
-0.43534234166145325,
-0.13457584381103516,
0.7774600982666016,
0.002244167495518923,
-0.07064279168844223,
-0.4638473391532898,
-0.3816007375717163,
-0.42950332164764404,
-0.32101351... |
In this task, you are given a set of context paragraph and some supporting facts to answer a question. Your task is to generate answer for given question based on set of context paragraphs and supporting facts.
Context_1 : Sausage Party is a 2016 American adult computer-animated comedy film directed by Greg Tiernan an... | 2016 | 0 | NIv2 | task170_hotpotqa_answer_generation | zs_opt | [
0.8316893577575684,
0.03666575998067856,
-0.2107747495174408,
-0.019705740734934807,
0.22016724944114685,
0.11568416655063629,
1.0124897956848145,
0.672520637512207,
-0.52071213722229,
0.540640115737915,
0.4047086238861084,
0.1243518739938736,
-0.5113065242767334,
-0.13733550906181335,
-... |
Given the task definition and input, reply with output. Given a review text from amazon and its polarity (either positive or negative). Generate answer "True" if given sentence and its polarity match, otherwise generate answer "False". A review is considered positive if the reviewer is satisfied with the product. Other... | False | 5 | NIv2 | task494_review_polarity_answer_generation | zs_opt | [
-1.0270048379898071,
0.39499998092651367,
0.7377516031265259,
-0.05602894723415375,
0.41250571608543396,
-0.3362957835197449,
1.077716588973999,
0.3615010976791382,
0.37290745973587036,
0.1315869688987732,
-0.4934404492378235,
-0.4571571946144104,
-0.43340253829956055,
-0.15584132075309753... |
In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Example: [5797, 8817, '8297', 'b', 'U', 'b'], [5843, 8809, '8297', 'b', 'W', 'C']
Example solution: 8297, b
Example explanation: Here, '8297, b' is the longest common subsequence in both the input lists [5797, 8817, '82... | Solution: 2093, 5929, 853, g, s, q, 1795, 75, 5073, 4799, z, 6829, 7865, 6801, f, b, W, 9629, V, 3931, P, I, 5783 | 5 | NIv2 | task605_find_the_longest_common_subsequence_in_two_lists | fs_opt | [
-0.12043925374746323,
0.058211229741573334,
-0.36048203706741333,
-0.6671773791313171,
-0.13293138146400452,
-0.24217447638511658,
0.14176031947135925,
0.9186751842498779,
-0.6449536681175232,
0.126435786485672,
-0.7505596876144409,
-0.012356402352452278,
0.02119499444961548,
0.31425088644... |
In this task, you are given one French sentence. The major part of the sentences talk about health-related topics, but some of the them describe an organization and its activities. Your job is to translate the given sentences into English.
Example input: La LGV est très rare en Europe.
Example output: LGV is very rare... | Ongoing calls for proposals | 3 | NIv2 | task1397_europa_ecdc_tm_fr_en_translation | fs_opt | [
-0.6081352233886719,
0.6614372134208679,
0.38019710779190063,
-0.287675678730011,
0.03699517995119095,
-0.10752729326486588,
0.15662993490695953,
-0.18817758560180664,
0.09744522720575333,
-0.08836977183818817,
-0.3295573592185974,
0.18868498504161835,
-0.5239120721817017,
0.45977219939231... |
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_basket | 9 | NIv2 | task152_tomqa_find_location_easy_noise | fs_opt | [
0.7214797735214233,
-0.367731511592865,
-0.48980504274368286,
-0.13321085274219513,
0.03644895181059837,
-0.33784720301628113,
0.7206335067749023,
0.48810920119285583,
-0.04371580854058266,
-0.10831069946289062,
-0.2355877310037613,
0.8957608342170715,
-0.1743265837430954,
0.01969458907842... |
We would like you to classify each of the following sets of argument pairs (discussing Gay Marriage) into either SIMILAR or NOT SIMILAR. A pair of arguments is considered SIMILAR if the arguments are about the same FACET (making the same argument), and is considered NOT SIMILAR if they do not have the same FACET. A FA... | Not similar | 3 | NIv2 | task147_afs_argument_similarity_gay_marriage | fs_opt | [
-0.8823384046554565,
0.7759527564048767,
0.5188521146774292,
-0.07489458471536636,
0.30479684472084045,
-0.3594397306442261,
0.17162007093429565,
0.6891565322875977,
-0.19064149260520935,
0.04688674211502075,
-0.9497624635696411,
0.5389916896820068,
-0.8658499717712402,
-0.9987667798995972... |
You are given a review of Amazon's food products. Your task is to divide them into two classes: negative or positive, depending on the content of the review.
Example Input: I agree with a previous reviewer - when it comes to the dinners (just about all of the Earth's Best choices) they are watery and SWEET. Apples (o... | Positive
| 3 | NIv2 | task586_amazonfood_polarity_classification | fs_opt | [
0.11296653747558594,
0.13531102240085602,
-0.11209865659475327,
-0.13830505311489105,
-0.19715456664562225,
-0.6828322410583496,
0.6842545866966248,
0.8948168754577637,
-0.2279517501592636,
0.4617575705051422,
0.17296959459781647,
0.01098678819835186,
-0.6593608856201172,
0.084127068519592... |
A text is given in English. Translate it from the English language to the Urdu language. The translation must not omit or add information to the original sentence.
One example is below.
Q: نئی دلّی ،23 مئیحکومت ہند کی جانب سے موجودہ انکم ٹیکس ایکٹ ، 1961 پر نظر ثانی اور ملک کی اقتصادی ضروریات کے عین مطابق نئی براہ راست... | Berhampur(Brahmapur Town) Odisha | 9 | NIv2 | task1058_pib_translation_urdu_english | fs_opt | [
0.4326856732368469,
-0.01538420282304287,
0.08543534576892853,
0.1707332730293274,
0.6853060722351074,
-0.9976832866668701,
0.6255091428756714,
1.1527819633483887,
-0.03642318770289421,
0.3572097718715668,
-0.291972279548645,
0.4748842716217041,
-0.5368492007255554,
0.5341167449951172,
-... |
In this task, you are given an input list A comprising of numbers and alphabets. You need to extract and sort the unique alphabets in the list. The alphabets in the input list will only be in lowercase. Return -1 if there is no alphabet in the input list.
Ex Input:
['o', 'd', '6495', '5211', '341', 'v', '385', 'v', 'g... | g, i, k, l, q, r, t, v, x, z
| 1 | NIv2 | task636_extract_and_sort_unique_alphabets_in_a_list | fs_opt | [
-0.15922705829143524,
0.0724458247423172,
-0.38666749000549316,
-0.20258872210979462,
0.09405545145273209,
-0.2673734128475189,
0.9720185995101929,
0.4613475799560547,
-0.4624832272529602,
0.31663215160369873,
-0.36526983976364136,
-0.09680552035570145,
-0.5759705901145935,
0.3190058469772... |
Teacher:In this task, you are given music product reviews in Japanese language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Teacher: Now, understand the problem? Solve this instance: ザクザクとした、説得力のあるヌルテ . スク... | POS | 6 | NIv2 | task487_cls_japanese_music_classification | zs_opt | [
0.12905555963516235,
0.04234003275632858,
-0.4827498197555542,
0.23357143998146057,
0.877650797367096,
-0.18852204084396362,
1.0083789825439453,
0.27000612020492554,
0.09699543565511703,
0.1934385448694229,
-0.38844746351242065,
-0.14574335515499115,
-0.16494247317314148,
-0.03637464717030... |
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