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 |
|---|---|---|---|---|---|---|
Classify the given news commentary into the language in which it is written in. There are 12 languages to classify the sentences into, 1) English, 2) French, 3) Arabic, 4) Czech, 5) German, 6) Spanish, 7) Dutch, 8) Portuguese, 9) Italian, 10) Zhuang, 11) Japanese, 12) Russian.
Input: Consider Input: 侨民是另一个发展融资的潜在主要来源。... | Output: Arabic
| 2 | NIv2 | task1370_newscomm_classification | fs_opt | [
-0.257769376039505,
-0.02887861058115959,
0.2848309278488159,
0.26379162073135376,
0.5755374431610107,
0.2622245252132416,
0.5188644528388977,
1.3551294803619385,
0.08492331206798553,
0.06632383167743683,
-0.19837376475334167,
0.483508825302124,
-0.5734548568725586,
-0.10082948207855225,
... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Adverse drug reactions are appreciably harmful or unpleasant reactions resulting from an intervention related to the use of medical products, which predicts hazard from future administration and warr... | non-adverse drug event | 0 | NIv2 | task1495_adverse_drug_event_classification | fs_opt | [
0.19734135270118713,
0.18883588910102844,
-0.671183705329895,
-0.9006490707397461,
-0.37967824935913086,
0.11137505620718002,
0.38617241382598877,
0.9365718960762024,
0.7754018902778625,
0.6655778884887695,
-0.5032870769500732,
0.1447654664516449,
0.13005366921424866,
0.1891154646873474,
... |
Instructions: In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Input: [7133, 'L', 'g', 'I', '8325', '1875', 'k', 1219], ['h', 'e', 'g', 'I', '8325', '1875', 'j', 9895]
Output: | g, I, 8325, 1875 | 3 | NIv2 | task605_find_the_longest_common_subsequence_in_two_lists | zs_opt | [
-0.9724903106689453,
0.16723963618278503,
-0.006472173612564802,
-0.863020658493042,
-0.32785850763320923,
-0.3651265501976013,
-0.032511238008737564,
-0.3775428533554077,
-0.8573868870735168,
-0.4492250382900238,
-1.1246976852416992,
-0.3265295624732971,
0.5261129140853882,
0.700455129146... |
In this task, you are given a context tweet, a question and corresponding answer of given question. Your task is to classify given passage into two categories: (1) "yes" if the given context is useful in answering the question, and (2) "no" if the given context is not useful.
[EX Q]: Context: CURRENT FRENCH TOAST ALER... | yes
| 6 | NIv2 | task242_tweetqa_classification | fs_opt | [
0.15394636988639832,
0.6457735300064087,
0.2517324984073639,
0.5313783884048462,
0.5462164282798767,
0.39419394731521606,
-0.005184818059206009,
-0.11088041961193085,
0.1011154055595398,
0.2916575074195862,
-0.20159587264060974,
-0.39936572313308716,
-0.5363764762878418,
-0.149340257048606... |
In this task, you need to count the number of times the given letter appears in the given sentence.
Example: Sentence: 'a large group of bananas proped up on several bicycles'. Find frequency of the letter 'e'
Example solution: 5
Example explanation: The letter 'e' appears 5 times in the sentence.
Problem: Sentence: '... | Solution: 2 | 5 | NIv2 | task113_count_frequency_of_letter | fs_opt | [
-0.09242570400238037,
0.2725817859172821,
-0.8095451593399048,
0.10856392979621887,
0.10786488652229309,
-0.8348009586334229,
0.7743631601333618,
0.6366983652114868,
-0.5728141069412231,
-0.057038553059101105,
-0.7395261526107788,
0.39641016721725464,
0.1616021692752838,
0.0100166508927941... |
Detailed Instructions: 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 ... | None | 8 | NIv2 | task1546_conll2002_location_name_extraction_answer_generation | zs_opt | [
0.23920318484306335,
0.46398550271987915,
-0.16277334094047546,
-0.09739319980144501,
-0.012015916407108307,
0.021184328943490982,
0.9322215914726257,
-0.16023290157318115,
0.7628154754638672,
-0.6886990666389465,
-0.6627172231674194,
0.7364616394042969,
-0.2115171104669571,
0.232170492410... |
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
Input: name[The Rice Boat], food[F... | The Rice Boat fast food has a customer rating of 1 out of 5, it is in the riverside area with and it is kid friendly | 2 | NIv2 | task957_e2e_nlg_text_generation_generate | zs_opt | [
-0.4654131531715393,
0.5253667831420898,
-0.39095091819763184,
0.04070047289133072,
0.0941166877746582,
-0.35252583026885986,
0.5167272686958313,
0.3514793813228607,
0.31358256936073303,
-0.05937206372618675,
0.08575600385665894,
-0.6708066463470459,
-0.7371399998664856,
0.0028016143478453... |
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.
--------
Question: Context_1 : Kevin Spacey Fowler, KBE (born July 26, 1959) is an American a... | Elizabeth Rodriguez starred as a series regular on an American postapocalyptic horror drama television series which is comprised of how many episodes in its first season?
| 7 | NIv2 | task191_hotpotqa_question_generation | fs_opt | [
0.11678760498762131,
0.41101694107055664,
-0.512001097202301,
0.18678657710552216,
0.4829709231853485,
0.5022682547569275,
0.2132420539855957,
0.6446196436882019,
-0.07841844856739044,
0.45685088634490967,
0.36231666803359985,
0.33181992173194885,
-0.5914462208747864,
0.37009650468826294,
... |
Q: 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: An actor (or actress for females; see terminology) is a person who portrays a characte... | serial killer | 7 | NIv2 | task1296_wiki_hop_question_answering | zs_opt | [
0.125532865524292,
0.6866858005523682,
-0.5437935590744019,
0.12790322303771973,
0.4057345986366272,
0.40065303444862366,
0.8747859001159668,
0.6872453093528748,
-0.15384048223495483,
0.25581008195877075,
0.3377962112426758,
0.2477860003709793,
-1.2482621669769287,
0.5292157530784607,
-0... |
You are given a sentence in English. Your job is to translate the English sentence into Hebrew.
Input: Consider Input: So, she's got a lure that she sticks out in front of this living mousetrap of needle-sharp teeth in order to attract in some unsuspecting prey.
Output: יש לו פיתיון שהוא מבליט בחזית של מלכודת עכברים ... | Output: מה הם היו מסוגלים לעשות עם התמונות שהם יכלו להראות אם היתה עומדת לרשותם תקשורת מודרנית כדי לשבות את ליבם ודעתם של הקהל?
| 2 | NIv2 | task1221_ted_translation_en_he | fs_opt | [
-0.3667318820953369,
0.7699056267738342,
-0.04220494627952576,
-0.18034228682518005,
-0.27558058500289917,
-0.005253545939922333,
0.12783211469650269,
0.05865621939301491,
0.1721244752407074,
-0.15956059098243713,
-0.22176794707775116,
0.17866826057434082,
-1.0120011568069458,
-0.445812612... |
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.
Example: フランスのパリ、パルク・デ・プランスで行われた2007年ラグビーワールドカップのプールCで、イタリアは31対5でポルトガルを下した。
Example solution: ອິຕາລີໄດ້ເສຍໃຫ້ປ໊ອກຕຸຍການ 31 ຕໍ່ 5 ໃນພູລ C ຂອງ ການແຂ່ງຂັນ... | Solution: ສະມາຄົມກ່າວວ່າການບໍລິຫານແມ່ນ "ຄອບງຳກັບການປະເຊີນເປົ້າໝາຍຂອງສູນຮັບແຈ້ງເພື່ອຈັດຫາການບໍລິການທີ່ມີຄຸນນະພາບດີພາຍໃນສັງຄົມ." | 5 | NIv2 | task1124_alt_ja_lo_translation | fs_opt | [
-0.784417986869812,
0.6099153757095337,
-0.6236616373062134,
0.07213899493217468,
-0.07216477394104004,
-0.34859704971313477,
0.4076350927352905,
0.4233889579772949,
0.03593967482447624,
-0.8165388107299805,
-1.1357088088989258,
0.9275991916656494,
-0.7900761365890503,
0.948757529258728,
... |
In this task you're given two statements in Gujarati. You must judge whether the second sentence is the cause or effect of the first one. The sentences are separated by a newline character. Output either the word 'cause' or 'effect' .
[Q]: સમુદ્રનું ભરતી જોખમી હતું.
તરવૈયાઓ કિનારા તરફ પાછા ફર્યા.
[A]: effect
[Q]: ... | cause
| 5 | NIv2 | task941_copa_gu_commonsense_cause_effect | fs_opt | [
-0.4966033697128296,
0.74906325340271,
-0.005896040704101324,
-1.0992088317871094,
-0.5931530594825745,
-0.9632980823516846,
0.43283742666244507,
0.47230851650238037,
-0.0717916414141655,
-0.48123684525489807,
-0.9208914041519165,
0.07711508870124817,
-0.7856292724609375,
0.064683690667152... |
Part 1. Definition
In this task, you're given the beginning and the ending of a three-part story. Your job is to complete the short story by writing a middle sentence that seamlessly connects the first and last sentence. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a ch... | It started to rain while they were in the woods. | 7 | NIv2 | task067_abductivenli_answer_generation | fs_opt | [
0.06089630722999573,
0.7274573445320129,
-0.2831462323665619,
-0.7393308877944946,
-0.4651453495025635,
0.2946630120277405,
0.5392857789993286,
0.3622419238090515,
-0.18785837292671204,
-0.5313088893890381,
-0.4101415276527405,
0.1286512166261673,
0.09678326547145844,
-0.05253593623638153,... |
Given a sentence in the Japanese, provide an equivalent translation in Bahasa Indonesia that retains the same meaning through the translation. In translation, keep numbers as it is.
Q: 脅迫状が米国の20の新聞に送られ、「ゴールドマン・サックス」と書かれていた。
A: Surat ancaman dikirim kepada 20 surat kabar menyatakan: "Goldman Sachs."
****
Q: 地方は政府のコントロ... | Formasi yang lebih kecil, dari bagian ekstrim Kanan dan ekstrim Kiri, mencoba menyebarkan ketakutan akan imigrasi dalam jumlah besar dan pengangguran.
****
| 4 | NIv2 | task1115_alt_ja_id_translation | fs_opt | [
-0.4505579471588135,
0.518444299697876,
-0.02634093537926674,
-0.8424135446548462,
-0.1886601597070694,
-0.7236557006835938,
0.37067922949790955,
0.10130345821380615,
-0.27826356887817383,
-0.16207951307296753,
-0.6723242402076721,
0.8774666786193848,
-0.9199933409690857,
-0.02406265027821... |
You are given a sentence in Galician. Your job is to translate the Galician sentence into Italian.
Q: En canto ás universidades, hai unhas 250 en todo o mundo que imparten cursos sobre videoxogos.
A: | Ci sono circa 350 scuole nel mondo che insegnano corsi di videogiochi. | 4 | NIv2 | task1243_ted_translation_gl_it | zs_opt | [
0.024065695703029633,
0.2760808765888214,
-0.9945385456085205,
-0.016505617648363113,
-0.7168443202972412,
-0.3705797493457794,
0.2605131268501282,
1.1177952289581299,
-0.8491188883781433,
-0.8819207549095154,
0.30419230461120605,
0.16322505474090576,
-0.11307213455438614,
0.10420656204223... |
In this task, you're given a text which is the body of the document. Indicate your answer as "Yes" if the text is about a person, otherwise indicate your answer as "No". Don't generate anything else apart from "Yes" or "No". Pay attention that for your answer to be "Yes", the passage should be generally about a person.... | No | 3 | NIv2 | task632_dbpedia_14_classification | fs_opt | [
-0.9609463810920715,
0.5764710903167725,
0.47673678398132324,
-0.6978281736373901,
0.023527756333351135,
-0.8549528121948242,
1.440739393234253,
0.21176612377166748,
0.01981981098651886,
-0.05344846844673157,
0.24125967919826508,
0.2879059314727783,
-0.3676373064517975,
0.1966681182384491,... |
You will be given a definition of a task first, then some input of the task.
In this task you are given a small conversation between two persons and 4 options on how the conversation should continue. Your job is to choose the most reasonable option. The conversation and the options are separated by a newline character.... | B | 1 | NIv2 | task611_mutual_multi_turn_dialogue | zs_opt | [
-0.0976676493883133,
-0.18993201851844788,
-0.3364907205104828,
-0.3607177734375,
0.4442085325717926,
-0.15226444602012634,
0.20638972520828247,
0.9367131590843201,
-0.06534577906131744,
0.2280663251876831,
-0.6969591379165649,
-0.43323978781700134,
-0.030144231393933296,
-0.46912503242492... |
instruction:
In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
question:
English: What gene(s) can we discover using relevant phenotypes (inclusive of drugs) to screen ENU mutageniz... | yes
| 9 | NIv2 | task831_giga_fren_classification | fs_opt | [
-0.6021125912666321,
0.5032017230987549,
0.2254912108182907,
-0.4544488787651062,
0.17197063565254211,
-0.4026017189025879,
0.3492600619792938,
0.5439707040786743,
0.4544849991798401,
0.43469351530075073,
-0.48824846744537354,
0.1405048370361328,
0.026357131078839302,
-0.2344483882188797,
... |
instruction:
In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In translation, keep numbers as it is.
question:
A fire in the plant allowed massive amounts of radiation to be released into the atmosphere .
answer:
संयंत्र में लगी एक आग से वातावरण में ... | यह माना जाता है कि बच्चन ने इस कार्यक्रम के संचालन के लिए साप्ताहिक प्रकरण के लिए अत्यधिक २५ लाख रुपए (२५ लाख रुपए भारतीय अमेरिकी डॉलर लगभग ६०००० ) लिए थे जिसके कारण बच्चन और उनके परिवार को नैतिक और आर्थिक दोनों रूप से बल मिला।
| 9 | NIv2 | task425_hindienglish_corpora_en_hi_translation | fs_opt | [
0.14359620213508606,
0.4150131344795227,
-0.014591537415981293,
-0.5206642150878906,
-0.4178183674812317,
-0.8330183625221252,
0.31042712926864624,
0.43233829736709595,
-0.54148930311203,
-0.328349769115448,
-0.6779696345329285,
0.24366134405136108,
-0.7699329257011414,
-0.0639804005622863... |
Detailed Instructions: The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (whereve... | No | 8 | NIv2 | task356_casino_classification_negotiation_self_need | zs_opt | [
0.07560119032859802,
0.2964284121990204,
-0.03321804106235504,
-0.28140366077423096,
-0.579693615436554,
-0.5674144625663757,
0.38291221857070923,
0.7119001150131226,
-0.5272958278656006,
0.2038453221321106,
0.27736949920654297,
-0.44816505908966064,
-0.9453524351119995,
-0.411872863769531... |
instruction:
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.
question:
What term is used to de... | hydroelectric
| 9 | NIv2 | task592_sciq_incorrect_answer_generation | fs_opt | [
0.5090906023979187,
1.4490596055984497,
-0.5413390398025513,
-0.4879629611968994,
-0.7777262926101685,
-1.0662550926208496,
0.4896617531776428,
-0.31985586881637573,
0.1955322027206421,
-0.5384378433227539,
-0.030975721776485443,
0.1905447542667389,
-0.7669865489006042,
-0.1197825521230697... |
Instructions: 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 la... | informal | 3 | NIv2 | task1533_daily_dialog_formal_classification | zs_opt | [
-0.2255045473575592,
0.5850767493247986,
-0.2432403564453125,
0.03617240488529205,
0.10893445461988449,
-0.44555696845054626,
0.598147988319397,
0.7165331840515137,
0.29591959714889526,
-0.06263796240091324,
-0.1315566748380661,
-0.08505016565322876,
-0.12968003749847412,
0.269555151462554... |
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 story, and th... | Solution: The children were napping in the car. After parking the car, the mother sees a posted sign. The sign says that deer hunting is today, so the trip is off. | 5 | NIv2 | task269_csrg_counterfactual_story_generation | fs_opt | [
0.8369448184967041,
0.08682620525360107,
-0.33178776502609253,
0.3679603934288025,
0.15309786796569824,
-1.2039446830749512,
0.3120187222957611,
1.3067195415496826,
-0.045399412512779236,
-0.01153909508138895,
-0.21673350036144257,
-0.033199287950992584,
-0.18132564425468445,
0.32083490490... |
In this task, you are given a sentence which is either in the Gujarati language or English language. You task is to identify the language of input sentence. Input sentence can be in Gujarari or English language only and also it cannot have two languages at a time.
[Q]: પૃષ્ઠભૂમિમાં ખુરશી પર બેસીને એક માણસ સાથે ચિત્ર મ... | English
| 5 | NIv2 | task441_eng_guj_parallel_corpus_gu-en_language_identification | fs_opt | [
-0.9529241919517517,
0.485377699136734,
0.764491081237793,
-0.5024757385253906,
0.1318301111459732,
-0.5413877367973328,
0.2497330605983734,
-0.16260814666748047,
0.12499663233757019,
-0.4201352000236511,
-0.4499542713165283,
0.32188838720321655,
-0.15324562788009644,
0.163691908121109,
... |
In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In the translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
One example: पहले दो को अविश्वसनीय मानकर बाकी पांच मुखबिरों के आधार पर मु... | With all sorts of pollution around , man continues to live without sparing any thought for it . | 6 | NIv2 | task424_hindienglish_corpora_hi_en_translation | fs_opt | [
0.2754405438899994,
0.2963476777076721,
0.9033403396606445,
-0.09694287925958633,
0.2112290859222412,
-0.45856744050979614,
-0.4179852604866028,
0.7049539089202881,
-0.4971570670604706,
-0.016500059515237808,
-0.8804471492767334,
-0.3392426669597626,
-0.2786521911621094,
0.0227525644004344... |
Detailed Instructions: A text is given in English. Translate it from the English language to the Panjabi language. The translation must not omit or add information to the original sentence.
See one example below:
Problem: ਸਾਥੀਓ , ਰਾਮਚਰਿਤ ਮਾਨਸ ਵਿੱਚ ਇੱਕ ਚੌਪਈ ਹੈ । ਗੋਸਵਾਮੀ ਤੁਲਸੀਦਾਸ ਜੀ ਨੇ ਲਿਖਿਆ ਹੈ ਕਿ ਭਗਵਾਨ ਰਾਮ ਕਿਸੇ ਦਾ ਵਿਅਕਤ... | The aim of the National Integration Tour is to promote harmony and awareness. | 4 | NIv2 | task1008_pib_translation_punjabi_english | fs_opt | [
-0.22867225110530853,
0.7016339898109436,
0.3397689461708069,
-0.3219751715660095,
-0.07949373126029968,
-0.2546544671058655,
0.4287458658218384,
0.4936288595199585,
-0.21963179111480713,
0.09845543652772903,
-0.490109384059906,
-0.18703116476535797,
-0.3682103455066681,
-0.502490758895874... |
Teacher:You are given a short poem which is written by a kid. Your task is to predict if the kid is in elementary school or high school. Anyone who is from grade 1st to 6th-grade will be considered as in elementary school, and 7th to 12th-grade kids will be considered as in high school. There are only two possible outp... | high | 6 | NIv2 | task1712_poki_classification | zs_opt | [
-0.16903306543827057,
0.9274812936782837,
0.4526844024658203,
-0.33177828788757324,
-0.358584463596344,
-0.5795838236808777,
0.30052101612091064,
0.8889427185058594,
0.5334175229072571,
-0.7758693695068359,
-0.41360485553741455,
0.5477800369262695,
-0.35403746366500854,
-0.3175511956214905... |
Detailed Instructions: You are given a sentence in English. Your job is to translate the English sentence into Hebrew.
Q: It's getting closer and closer, and in 20...
A: | זה מתקרב יותר ויותר, וב-20.... | 9 | NIv2 | task1221_ted_translation_en_he | zs_opt | [
-0.1049046516418457,
1.3608644008636475,
0.052924759685993195,
0.16582342982292175,
-0.38721227645874023,
-0.5764544606208801,
0.2423078715801239,
0.3019934594631195,
0.5764790773391724,
0.2167789340019226,
0.21280638873577118,
0.5063866376876831,
-0.8274544477462769,
-0.3748488426208496,
... |
Definition: You will be given one or more triples. The second part of each triple shows the relation between the first and the third element. Your task is to write a simple and short piece of text (sentence(s)) that describes the triples in natural language.
Input: School of Business and Social Sciences at the Aarhus U... | The School of Business and Social Sciences at Aaarhus University is located in Aarhus, Denmark. | 2 | NIv2 | task1728_web_nlg_data_to_text | zs_opt | [
-0.7413666248321533,
0.6001588106155396,
-0.3693190813064575,
-1.442403793334961,
-0.48188817501068115,
0.6714872121810913,
1.0965445041656494,
-0.44532424211502075,
-0.1366363763809204,
0.13863539695739746,
-0.4716646075248718,
0.45839744806289673,
-0.4626171290874481,
0.21859727799892426... |
Given the task definition and input, reply with output. 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 par... | Alot of work, but very rewarding!! | 5 | NIv2 | task1729_personachat_generate_next | zs_opt | [
-0.11841247975826263,
0.5934052467346191,
-0.26619887351989746,
-0.027529194951057434,
-0.4176228642463684,
-0.12712161242961884,
0.7840555906295776,
0.37394797801971436,
-0.7564799785614014,
-0.47875964641571045,
0.19808311760425568,
-0.12742950022220612,
-0.654738187789917,
-0.4735632538... |
You are given a sentence in Galician. Your job is to translate the Galician sentence into English.
One example: Agora, está ao lado, ou na miña casa.
Solution is here: Now, it's next door, or in my house.
Explanation: The Galician sentence is correctly translated into English. `casa` is correctly translated as `house`.... | It was when I was on holiday last early autumn in France. | 6 | NIv2 | task1238_ted_translation_gl_en | fs_opt | [
-0.4203021824359894,
1.2909631729125977,
-0.16228362917900085,
-0.7961577773094177,
-0.08014035224914551,
-1.2901504039764404,
0.3684099614620209,
0.8724191188812256,
-0.28945592045783997,
0.03462165594100952,
-0.30807167291641235,
0.43991369009017944,
-0.9793299436569214,
0.05908603221178... |
Instructions: You are given a sentence in English. Your job is to translate the English sentence into Polish.
Input: And then the important third dimension.
Output: | Czas na ważny, trzeci wymiar. | 3 | NIv2 | task1092_ted_translation_en_pl | zs_opt | [
-0.13200311362743378,
0.5743302702903748,
-0.05878966301679611,
-0.23170530796051025,
-0.08787773549556732,
0.18874046206474304,
0.735819935798645,
-0.7222439646720886,
-0.3225013017654419,
-0.001082992646843195,
-0.27190306782722473,
0.6384596824645996,
-0.6090342402458191,
0.089485578238... |
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... | When rocks are weathered and eroded they break down into smaller pieces of rocks and minerals. | 4 | NIv2 | task037_qasc_generate_related_fact | zs_opt | [
0.13267399370670319,
0.9897688627243042,
-0.7502421140670776,
-0.006412339396774769,
-0.4510553479194641,
-1.7024211883544922,
0.05350271612405777,
0.776681661605835,
-0.5229527950286865,
-0.016521835699677467,
-0.6602994799613953,
0.5852178335189819,
-0.22821927070617676,
0.27546700835227... |
Detailed Instructions: You are given a sentence in Polish. Your job is to translate the Polish sentence into Japanese.
Problem:(Śmiech) W każdym razie, nie wiem, co powiedzą o mnie moi przyjaciele, jak dowiedzą się o tej prezentacji.
Solution: | （ 笑 ） 後で友人達に何と言われるかわかりませんが | 8 | NIv2 | task1257_ted_translation_pl_ja | zs_opt | [
-0.2404840886592865,
0.3625379204750061,
0.045020416378974915,
-0.5294841527938843,
-0.21245414018630981,
-0.01711191050708294,
1.3472844362258911,
-0.44775572419166565,
0.5404964089393616,
-0.7145450115203857,
-0.15640954673290253,
0.08066260814666748,
-0.572784423828125,
0.40423145890235... |
Definition: This task is about creating an unanswerable question based on a given passage. Construct a question that looks relevant to the given context but is unanswerable. Following are a few suggestions about how to create unanswerable questions:
(i) create questions which require satisfying a constraint that is not... | What is the Union based upon? | 2 | NIv2 | task348_squad2.0_unanswerable_question_generation | zs_opt | [
0.28032392263412476,
0.08611766993999481,
-0.6342618465423584,
0.3784141540527344,
-0.16834717988967896,
-0.6027354001998901,
0.7891384363174438,
1.3891987800598145,
-0.29567259550094604,
0.09368787705898285,
-0.1600915789604187,
0.09434760361909866,
-0.3658926784992218,
-0.228562414646148... |
Definition: In this task you will be given a string of characters. You should remove all vowels from the given string. Vowels are: i,e,a,u,o. The character 'y' or 'Y' does not count as a vowel.
Input: MeBchqtdTcEIKCXrXnqa
Output: | MBchqtdTcKCXrXnq | 2 | NIv2 | task365_synthetic_remove_vowels | zs_opt | [
0.6559000611305237,
0.914397120475769,
-0.49137264490127563,
-0.667923092842102,
0.5491260886192322,
-0.6655723452568054,
0.45460227131843567,
0.46025437116622925,
0.4505440592765808,
-0.2371854931116104,
-0.41107678413391113,
-0.37421226501464844,
0.041479792445898056,
-0.7067257761955261... |
You will be given a definition of a task first, then some input of the task.
The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent ... | No | 1 | NIv2 | task359_casino_classification_negotiation_vouch_fair | zs_opt | [
0.0018319273367524147,
0.477708101272583,
-0.08786184340715408,
-0.09308468550443649,
-0.6494778394699097,
-0.21151100099086761,
1.1196321249008179,
0.5126388072967529,
0.3094334006309509,
0.22638362646102905,
0.297861784696579,
-0.1066938042640686,
-0.5811150074005127,
-0.2269018292427063... |
Part 1. Definition
You're given a sentence and your task is to classify whether the sentence is acceptable or not. Any sentence which is grammatically correct, has a naturalistic text, is written by a native speaker and which minimizes superfluous content is acceptable, otherwise unacceptable. If the sentence is accept... | acceptable | 7 | NIv2 | task616_cola_classification | fs_opt | [
-0.18984274566173553,
0.47756290435791016,
0.6619900465011597,
-0.5630539655685425,
0.5604696869850159,
-1.0631859302520752,
0.4713701605796814,
0.26691102981567383,
0.6591425538063049,
0.34086841344833374,
-0.7095961570739746,
-0.4276003837585449,
-0.2951037883758545,
-0.3002101182937622,... |
Teacher: You are given a sentence in Persian. Your job is to translate the Farsi sentence into Italian.
Teacher: Now, understand the problem? If you are still confused, see the following example:
این یک خانه ی اسکیمو می شود.
Solution: Così diventa un igloo.
Reason: The Farsi sentence is correctly translated into Italia... | Se avessi avuto le informazioni giuste, avresti fatto la cosa giusta. Infine, voi volete essere quello che si prende cura degli altri. | 2 | NIv2 | task1271_ted_translation_fa_it | fs_opt | [
-0.12228870391845703,
0.2798466980457306,
-0.39157649874687195,
-0.10475257784128189,
-0.3336089849472046,
-1.2177541255950928,
0.32811468839645386,
0.41256821155548096,
-0.13075029850006104,
-0.249435156583786,
-0.18669095635414124,
1.0085570812225342,
-0.8341345191001892,
0.0418160557746... |
You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Japanese.
One example: كان الأمر كزيارة أكثر عصور البراءة على كوكب الأرض
Solution is here: 地球が今よりも無垢だった時代を訪れたかのようでした
Explanation: The Arabic sentence is correctly translated into Japanese, because the meaning is preserved.
Now, solve... | こちらは山 | 6 | NIv2 | task1231_ted_translation_ar_ja | fs_opt | [
0.027140077203512192,
0.6408257484436035,
-0.5465749502182007,
-0.575525164604187,
-0.6088796257972717,
-0.6984896063804626,
0.9918767809867859,
-0.2229294627904892,
0.07918305695056915,
-0.4045276641845703,
-0.9084270596504211,
0.12143063545227051,
-0.510838508605957,
0.29989463090896606,... |
Translate from Hindi to English such that it preserves the original meaning Perform complete translation (partially translated sentences are considered incorrect).
Ex Input:
मुझे संदेह है.
Ex Output:
I have my doubts.
Ex Input:
कल रात तुम "नया घर" गये थे?
Ex Output:
Have you been to the "new home" last night?
E... | I have not used till now.
| 1 | NIv2 | task1323_open_subtitles_hi_en_translation | fs_opt | [
-0.2996956408023834,
0.5224323272705078,
-0.024119794368743896,
0.6563205718994141,
-0.23951803147792816,
-0.680269181728363,
0.5428724884986877,
0.062391795217990875,
-0.4466206431388855,
-0.4805793762207031,
-0.3994928002357483,
0.5193122029304504,
-1.164952278137207,
0.09400380402803421... |
Instructions: 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.
Input: Sentence 1: Berman locates his ... | slate | 3 | NIv2 | task197_mnli_domain_answer_generation | zs_opt | [
-0.39749377965927124,
0.638983428478241,
-0.024522708728909492,
-0.7196722030639648,
-0.15592649579048157,
0.10506783425807953,
-0.18553227186203003,
0.35722529888153076,
0.37842461466789246,
-0.12093229591846466,
-0.46249842643737793,
-0.06419558078050613,
-0.5807877779006958,
-0.31982508... |
A text is given in English. Translate it from the English language to the Hindi language. The translation must not omit or add information to the original sentence.
--------
Question: लाओ पिडीआर के कृषि एवं वानिकी मंत्री माननीय लियाने थाइक्यो।
Answer: LianeThykeo, Minister of Agriculture and Forestry, Lao PDR
Questi... | Minister Jal Shakti stresses need to make Water Conservation a Jan Andolan like Swachh Bharat
| 7 | NIv2 | task1024_pib_translation_hindi_english | fs_opt | [
-0.4117213487625122,
0.31396350264549255,
0.30317044258117676,
-1.2754201889038086,
-0.353341281414032,
-0.36980122327804565,
0.34334468841552734,
0.38253891468048096,
-0.7166985273361206,
0.5165175199508667,
-0.1988113671541214,
-0.4148213565349579,
-1.0282832384109497,
0.7420370578765869... |
You will be given a definition of a task first, then some input of the task.
In this task, you're given a sentence and your task is to generate a simplified sentence that focuses on lexical paraphrasing from the original sentence given in the input.
during an interview , edward gorey mentioned that bawden was one of h... | during an interview edward gorey mention that bawden is one of his favorite artists. | 1 | NIv2 | task934_turk_simplification | zs_opt | [
-0.47510814666748047,
0.522212028503418,
-0.1861812174320221,
-1.0301709175109863,
0.5181519985198975,
0.037033550441265106,
1.130741834640503,
-0.16394361853599548,
0.2708800137042999,
-0.38222646713256836,
-0.3708564043045044,
0.1612367331981659,
-0.006304796785116196,
-0.152378350496292... |
Instructions: This task is about translating a given Spanish language sentence to English.
Input: Si eso es nuevo para ti, entonces necesitas desarrollar esta referencia mental, pero es fácil, simplemente haz unas tomas de muestra.
Output: | If that's new to you them you need to build at this mental reference but that's easy just make a couple of example shoots. | 3 | NIv2 | task1692_qed_amara_translation | zs_opt | [
-0.7351934313774109,
0.7429490089416504,
0.282652884721756,
-0.36208781599998474,
0.08565374463796616,
-0.7813324928283691,
0.5721819996833801,
1.065420389175415,
0.403134286403656,
-0.6336797475814819,
-0.3126643896102905,
-0.11173858493566513,
-0.5720109343528748,
0.19152995944023132,
... |
Instructions: In this task, you are given a question in Persian, and your task is to translate it into English.
Input: استراتژی شما در مورد Bachelor \ Bachelorette چه خواهد بود؟
Output: | What would be your strategy on either The Bachelor\Bachelorette? | 3 | NIv2 | task653_parsinlu_fa_en_translation | zs_opt | [
-0.2894664406776428,
1.0124423503875732,
-0.07976185530424118,
-0.4125363826751709,
-0.19320546090602875,
0.186575785279274,
0.6231629848480225,
0.3469506502151489,
0.5982624292373657,
0.4642185568809509,
0.27908796072006226,
0.7374224662780762,
0.11362776160240173,
-0.33120161294937134,
... |
Find the movie name from the given conversation. If the movie name is not found give output as "unknown"
Q: ASSISTANT: What kind of movies do you tend to watch? , USER: I enjoy superhero movies. , ASSISTANT: Have you seen The Predator? , USER: No, I haven't. , ASSISTANT: Have you seen The Dark Knight? , USER: Yes, I ha... | The Dark Knight | 4 | NIv2 | task926_coached_conv_pref_word_generation | zs_opt | [
-0.03499346971511841,
0.39756613969802856,
-0.5179336071014404,
0.006594817154109478,
-0.5661609172821045,
-0.26538795232772827,
1.1450228691101074,
-0.022070415318012238,
0.33227601647377014,
0.31873267889022827,
-0.05964944511651993,
-0.7082616686820984,
-1.046523094177246,
-0.0226467326... |
Teacher:In this task, you will be given a short story. One sentence from the story is chosen. Consider the events that happen after that sentence. Is any of them directly caused by it, or is made possible by it? You should write your answer in the form " A >causes/enables> B". Try to use phrases and sentences from the ... | Joe needs to go to basketball practice >Causes/Enables> He asks his cousin to take him to basketball practice | 6 | NIv2 | task748_glucose_reverse_cause_event_detection | zs_opt | [
0.1307334452867508,
0.301484614610672,
-0.24661791324615479,
-0.4087589979171753,
-0.08447350561618805,
-1.247610330581665,
-0.11197719722986221,
1.2687411308288574,
-0.047515869140625,
-0.0004514581523835659,
-0.6397390365600586,
-0.2568895220756531,
-0.3729569911956787,
-0.49891236424446... |
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.
Example Input: Context_1 : Netzach (Hebrew: נצח , "eternity") is the seventh of the ten S... | The star of the sports film Crooked Arrows grew up in what state?
| 3 | NIv2 | task191_hotpotqa_question_generation | fs_opt | [
0.07623444497585297,
0.4708218574523926,
-0.47132056951522827,
0.10650108754634857,
0.2028130143880844,
0.05460147559642792,
0.9902101159095764,
0.8449509143829346,
-0.01644863374531269,
0.5491898059844971,
-0.33198773860931396,
1.0152909755706787,
-1.195873498916626,
0.5431373119354248,
... |
Definition: In this task you will be given a list of numbers and you need to subtract every value in the list with the index it is at. The index of an elements shows its numerical order in the list(for example, in the list [7,10,4,5], the index of 7 is 1 and the index of 4 is 3) You should start the index at 1, so the... | [1, 11, 13, -11] | 2 | NIv2 | task096_conala_list_index_subtraction | zs_opt | [
0.1726701557636261,
0.36175715923309326,
-0.7283292412757874,
-0.1211399957537651,
0.25544261932373047,
-0.03824802488088608,
1.1289536952972412,
0.38117367029190063,
0.6162588000297546,
-0.06406041979789734,
-0.4110027551651001,
-0.35693198442459106,
-0.3932228684425354,
0.396905839443206... |
Detailed Instructions: In this task, you're given a passage, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both passage and link info... | How many citizens lived in Essex the year Whitehouse's family moved to that city? | 4 | NIv2 | task236_iirc_question_from_passage_answer_generation | fs_opt | [
0.2409922033548355,
0.8207013607025146,
-0.6906018853187561,
0.09910236299037933,
0.19505172967910767,
-0.914901852607727,
0.8025187253952026,
1.0988953113555908,
0.26380935311317444,
0.26268327236175537,
-0.5828680992126465,
0.4196053743362427,
-0.6169226169586182,
0.16782763600349426,
... |
Detailed Instructions: In this task, you are given a hateful post in Bengali that expresses hate or encourages violence in a geopolitical context based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: geopolitical or non-geopol... | non-geopolitical | 8 | NIv2 | task1493_bengali_geopolitical_hate_speech_binary_classification | zs_opt | [
-0.2776290476322174,
0.06149294227361679,
0.1683453917503357,
0.15701213479042053,
-0.6122444868087769,
-0.2730104625225067,
-0.46375155448913574,
0.3200174570083618,
-0.03315282613039017,
0.03651687502861023,
-0.6004279851913452,
-0.7698357105255127,
-0.3229300379753113,
-0.60773897171020... |
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).
Example input: पहले दो को अविश्वसनीय मानकर बाकी पांच मुखबिरों के आधार पर... | No co-ordinated railway policy was possible because of the multiple ownership and management of the railways . | 3 | NIv2 | task424_hindienglish_corpora_hi_en_translation | fs_opt | [
0.2552739381790161,
0.38024038076400757,
0.5267502069473267,
-0.5247767567634583,
0.14328783750534058,
-0.2636782228946686,
-0.42168137431144714,
0.923849880695343,
0.0632055252790451,
-0.03237317502498627,
-0.7870710492134094,
-0.2666468918323517,
0.07302907109260559,
0.13119107484817505,... |
In this task, you're given a question, along with a context passage. The passage will not have a direct answer to the question, but can include some information and a clue for the answer. Assuming you can only obtain information about one entity in the passage, your job is to determine whether information from the pass... | b
| 3 | NIv2 | task233_iirc_link_exists_classification | fs_opt | [
0.40849509835243225,
-0.5215979218482971,
-0.3549517095088959,
-0.29696810245513916,
0.6543934941291809,
-0.27866798639297485,
0.9126061797142029,
1.3250337839126587,
-0.1932474821805954,
0.5988436341285706,
-0.6507580876350403,
0.07450240850448608,
-0.1377357542514801,
0.07802830636501312... |
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.
Example: అనేకవింతపురాణములు భారతదేశం యొక్క ఈ అరణ్య యొక్క చెప్పబడ్డాయి, కానీమోగ్లీఅనేచిన్నబాలుడుకథ కాబట్టి వింత
Example solu... | Solution: Those are money transfers. | 5 | NIv2 | task1324_open_subtitles_te_en_translation | fs_opt | [
-0.34789443016052246,
1.0071439743041992,
0.3103492259979248,
0.25392812490463257,
0.05991675704717636,
-1.4561985731124878,
0.14486205577850342,
-0.0071215759962797165,
-0.4513113498687744,
-0.5147479176521301,
-0.6589736938476562,
-0.07972119003534317,
-0.8112183809280396,
-0.12961530685... |
In this task you will be given some text dialogue and you need to infer the underlying emotion of the text. The possible emotions are happy, sad, angry, or other.
did you miss me yes miss i miss you too babe | sad | 0 | NIv2 | task517_emo_classify_emotion_of_dialogue | zs_opt | [
-0.6161311864852905,
0.6048920154571533,
0.28981813788414,
-0.2631385922431946,
0.40807774662971497,
-0.12176036834716797,
1.3130208253860474,
0.16258835792541504,
0.4081382751464844,
0.38116902112960815,
-0.5663121342658997,
-0.3610765337944031,
-0.5777350664138794,
0.053264860063791275,
... |
In this task, you will be given a list. The list is several integers and letters separated with a comma, written within a []. You can create new lists by dropping one of the items in the input list. Your task is to write a list containing all the possible lists you can make by dropping one item from the input list. Fo... | Output: [['J', 'e', '8', 'Q', 'L', 'a'], ['J', 'e', '8', 'Q', 'L', '0'], ['J', 'e', '8', 'Q', 'a', '0'], ['J', 'e', '8', 'L', 'a', '0'], ['J', 'e', 'Q', 'L', 'a', '0'], ['J', '8', 'Q', 'L', 'a', '0'], ['e', '8', 'Q', 'L', 'a', '0']]
| 2 | NIv2 | task208_combinations_of_list | fs_opt | [
0.11636485904455185,
0.39939427375793457,
-0.5659581422805786,
0.5156795978546143,
0.6927914619445801,
-0.362387090921402,
0.8454402089118958,
0.8063710331916809,
-0.33827757835388184,
0.13113200664520264,
-0.3509485721588135,
-0.08702898025512695,
-0.057843200862407684,
-0.261059254407882... |
In this task, you're given a context passage. Your job is to generate relevant questions that can be answered by directly referring to the passage.
One example: Tracy slept awkwardly on their new bed and was having some pain, so Tracy cracked her neck.
Solution is here: What did Tracy do with her neck?
Explanation: The... | What may be reason information is being given about Rudy ? | 6 | NIv2 | task596_mocha_question_generation | fs_opt | [
0.14536812901496887,
1.0987651348114014,
-0.11941622197628021,
0.11190687865018845,
-0.1563313752412796,
-0.1755952537059784,
0.5330584049224854,
0.3391066789627075,
-0.07426268607378006,
-0.036283690482378006,
-0.7348877191543579,
0.18351930379867554,
-0.3579520583152771,
0.27828526496887... |
Detailed Instructions: In this task, you are given a sentence with a missing word that can be an object, a person, and/or an action. Fill in the blank with a plausible word. Although each sentence has many correct answers, you only have to write one answer.
Problem:PersonX sees ___ behind PersonY
Solution: | dog | 8 | NIv2 | task1217_atomic_answer_generation | zs_opt | [
0.21284182369709015,
0.7516884803771973,
0.14412972331047058,
-0.38623785972595215,
-0.29707473516464233,
0.2764695882797241,
1.1777920722961426,
0.6138193607330322,
0.19429393112659454,
-0.5429959893226624,
-0.08777038007974625,
-0.9444218873977661,
-0.2642936408519745,
0.3911636471748352... |
Detailed Instructions: 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... | Yes | 8 | NIv2 | task1196_atomic_classification_oeffect | zs_opt | [
0.5017161965370178,
0.7022513747215271,
0.16238154470920563,
-0.269405722618103,
-0.3924557566642761,
-0.7346213459968567,
1.235482931137085,
0.323738157749176,
-0.5675891637802124,
-0.30521196126937866,
-0.4806405305862427,
0.022797100245952606,
-0.8461640477180481,
-0.09162863343954086,
... |
Given the task definition and input, reply with output. In this task, you are given a sentence from the research paper and your task is to classify the given sentence into the following categories: Background (Why is this problem important? What relevant works have been created before? What is still missing in the prev... | background | 5 | NIv2 | task1163_coda19_section_classification | zs_opt | [
-0.24380233883857727,
0.5594478249549866,
0.2508796751499176,
-0.5574880838394165,
-0.07916882634162903,
0.36593157052993774,
0.34690436720848083,
0.6079671382904053,
0.38421499729156494,
-0.24556298553943634,
-1.1795581579208374,
0.1998026818037033,
-0.0775180533528328,
0.0188573207706213... |
instruction:
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 answer the given question. A good incorrect answer should be cl... | Yes.
| 9 | NIv2 | task057_multirc_classify_incorrect_answer | fs_opt | [
0.5150503516197205,
0.6762504577636719,
-0.3273380994796753,
-0.08841890096664429,
0.30819836258888245,
-0.6722313165664673,
0.6736854314804077,
0.8403881192207336,
0.03610263019800186,
0.11472085863351822,
-0.39569082856178284,
0.5013738870620728,
-0.27180880308151245,
0.29967451095581055... |
In this task, you're given passages that contain mentions of names of people, places, or things. Some of these mentions refer to the same person, place, or thing. Your job is to write questions that evaluate one's understanding of such references. Good questions are expected to link pronouns (she, her, him, his, their,... | What's the name of the person the hitchhiker is hunting?
| 7 | NIv2 | task001_quoref_question_generation | fs_opt | [
0.22482173144817352,
0.3975415825843811,
-0.5670241713523865,
0.2187078297138214,
0.812873125076294,
-0.07311077415943146,
0.6678733229637146,
1.0884041786193848,
0.14787743985652924,
0.6699568629264832,
-0.4558600187301636,
0.19490888714790344,
-0.6337498426437378,
0.034353114664554596,
... |
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 t... | No | 6 | NIv2 | task1205_atomic_classification_isafter | zs_opt | [
0.3363826870918274,
0.15713715553283691,
0.22407153248786926,
-0.35556596517562866,
-0.6740164160728455,
-0.8224518895149231,
1.3350732326507568,
0.39908984303474426,
-0.6100754737854004,
-0.5455881357192993,
-0.3498724400997162,
-0.437341570854187,
-0.6675845980644226,
0.10362839698791504... |
Teacher: You are given a sentence in English. Your job is to translate the English sentence into Polish.
Teacher: Now, understand the problem? If you are still confused, see the following example:
It's sort of the biggest TiVo box you've ever seen.
Solution: To największa nagrywarka, jaką w życiu widzieliście.
Reason: ... | Niestety, w czasie implementacji programista był lekko wstawiony i udało mu się zapomnieć wszystkich wyuczonych zasad bezpiecznego programowania, | 2 | NIv2 | task1092_ted_translation_en_pl | fs_opt | [
-0.2965753674507141,
0.41852641105651855,
0.40180644392967224,
0.05779893696308136,
0.38234224915504456,
-0.6176590919494629,
0.30796024203300476,
-0.04966173693537712,
0.11186966300010681,
0.296730637550354,
0.6094954013824463,
0.3690270185470581,
-0.6396245956420898,
-0.10325367748737335... |
Classify the given tweet into the three categories: (1) 'Hate Speech', (2) 'Offensive' and (3) 'Neither'. 'Hate Speech' is kind of a threating statement or sometimes include call for violence while 'offensive' statement just offensds someone. 'Neither' is when it doesn't fall into Hate Speech or Offensive category.
Ex... | Offensive
| 1 | NIv2 | task904_hate_speech_offensive_classification | fs_opt | [
-0.33278822898864746,
0.33347272872924805,
0.4627123475074768,
0.3132966160774231,
-0.2287435233592987,
-1.2324211597442627,
-0.485071063041687,
0.9262532591819763,
0.2700432538986206,
0.41511714458465576,
-0.5799255967140198,
-0.27670973539352417,
-0.6331689357757568,
-0.8941826820373535,... |
Detailed Instructions: In this task, you are given a sentence from the Quran in Persian, and your task is to translate it into English.
Q: و همانا بر تو آیاتى روشن فرو فرستادیم، و جز فاسقان [کسى] آنها را انکار نمىکند.
A: | We have sent clear signs to you, such as none can deny except those who transgress the truth. | 9 | NIv2 | task657_quran_fa_en_translation | zs_opt | [
-0.3101813793182373,
0.9096519351005554,
0.3212790787220001,
-0.32756146788597107,
-0.8455310463905334,
-0.3649566173553467,
0.9481710195541382,
0.44440150260925293,
0.32973819971084595,
-0.030899692326784134,
-0.5644227862358093,
0.8169715404510498,
-0.7248092889785767,
0.6530814170837402... |
Instructions: In this task, you are given a word, followed by a sentence. You should respond with a valid sentence which contains the word with the same meaning as in the given sentence. For example, if the given sentence refers to a 'fly' as the insect, you should not respond with a sentence which uses 'fly' as the ve... | He is studying for the ministry. | 3 | NIv2 | task627_xlwic_word_with_same_meaning_sentence_generation | zs_opt | [
-0.5328897833824158,
0.922589898109436,
0.19307217001914978,
-0.8828246593475342,
-0.4530673623085022,
-1.0132821798324585,
0.11591491848230362,
0.10222196578979492,
0.07068900018930435,
-0.432422935962677,
-0.27117934823036194,
0.18959486484527588,
-0.46721553802490234,
0.2728417515754699... |
Given a real-life anecdote of a complex ethical situation, generate a suitable title that describes the main event/root cause of the situation. Imagine that the given text is a social media post, and you have to write the title of the post, so the users can decide to read the main text or not.
I let him know that our ... | not updating/texting my husband for 3 and a half hours when I was out | 0 | NIv2 | task500_scruples_anecdotes_title_generation | zs_opt | [
-0.006257189437747002,
0.17370447516441345,
-0.23290136456489563,
-0.14713504910469055,
0.4795902371406555,
-0.3907778263092041,
0.09858393669128418,
0.8246195316314697,
-0.025338064879179,
0.29304200410842896,
-0.14611071348190308,
0.8454197645187378,
-1.429600715637207,
-0.24272936582565... |
Given the task definition and input, reply with output. Given a factoid/trivia type question, generate the topic of the question. The topic is the entity the question talks about.
What was the job of Chesley B Sullenberger III that made him famous on 15 January 2009?
| chesley sullenberger | 5 | NIv2 | task899_freebase_qa_topic_generation | zs_opt | [
-0.07815967500209808,
0.8927212953567505,
-0.36923646926879883,
0.25630512833595276,
-0.7580433487892151,
-0.17442505061626434,
0.018934229388833046,
-0.24796831607818604,
0.2063249945640564,
-0.7064541578292847,
-0.38199853897094727,
0.8677999973297119,
-0.16720211505889893,
-0.3480085432... |
Given the task definition and input, reply with output. Given a sentence in Russian, generate a new Russian 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 plau... | Люди предпочитают спать в темноте. | 5 | NIv2 | task410_mickey_ru_sentence_perturbation_generation | zs_opt | [
-0.4751615822315216,
0.5378793478012085,
0.24311813712120056,
-0.17693990468978882,
-0.765083909034729,
0.42511212825775146,
0.5442068576812744,
1.25069260597229,
0.5892668962478638,
-0.3078117370605469,
-1.5878572463989258,
-0.010612077079713345,
-0.47346875071525574,
0.06579765677452087,... |
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 Farsi.
Herdei a paixão dele pela manufatura, mas esta arte está em extinção.
Output: | با این وجود من عشقی که اون برای تولید داشت رو به ارث بردم ، جز اینکه عشقی به اون اندازه دیگه وجود نداره. | 1 | NIv2 | task1282_ted_translation_pt_fa | zs_opt | [
-0.6054295301437378,
0.6705769300460815,
-0.0594833567738533,
-0.13155683875083923,
-0.21601831912994385,
0.5460764169692993,
0.3085407614707947,
0.5561124682426453,
0.44453921914100647,
0.05725447088479996,
-1.1390000581741333,
-0.10098601877689362,
0.03487016260623932,
0.8503749966621399... |
Detailed Instructions: In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the ev... | Yes | 8 | NIv2 | task1201_atomic_classification_xintent | zs_opt | [
0.4893672466278076,
0.4090012013912201,
0.39732182025909424,
-0.26028189063072205,
-0.790438175201416,
-0.7172669172286987,
1.3689076900482178,
0.15359161794185638,
-0.3104369044303894,
-0.34747448563575745,
-0.05063718557357788,
-0.477205365896225,
-0.9844379425048828,
0.3699069321155548,... |
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: I have bought several of the Vitality canned dog food products and have found them all to be of good quality. The product looks more like a stew than a p... | Solution: Negative | 5 | NIv2 | task586_amazonfood_polarity_classification | fs_opt | [
-0.32561320066452026,
-0.31246596574783325,
0.245078444480896,
-0.5864864587783813,
0.14699283242225647,
-0.26844796538352966,
0.9018168449401855,
0.6040769815444946,
-0.06154739111661911,
0.5581870675086975,
0.13608333468437195,
-0.15402880311012268,
-0.6859630942344666,
-0.29747855663299... |
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.
Q: Sentence: 'a man wearing brown is skating in a park'. How many words end with the letter 'n' in the sentence.
A: | 3 | 4 | NIv2 | task163_count_words_ending_with_letter | zs_opt | [
0.5535616278648376,
0.8960684537887573,
0.2459002435207367,
-0.7801135778427124,
-0.3275209665298462,
-0.2026669681072235,
-0.05657398700714111,
-0.07520186901092529,
0.5526759028434753,
-0.3431776762008667,
-0.5837748646736145,
0.026699349284172058,
-1.2049647569656372,
0.1273289620876312... |
Given a premise, an initial context, an original ending, and a new ending, the task is to generate the counterfactual context that is aligned with the new ending. Each instance consists of a five-sentence story. The premise is the first sentence of a story, and the second sentence, which is the initial context, provide... | She wondered what her father had left her. | 0 | NIv2 | task270_csrg_counterfactual_context_generation | zs_opt | [
0.23544535040855408,
0.11848898977041245,
-0.2152889370918274,
0.36939090490341187,
-0.00013554934412240982,
-1.0295119285583496,
0.06725218892097473,
1.0759767293930054,
0.07695889472961426,
-0.04532908275723457,
-0.24644717574119568,
-0.06106191873550415,
-0.7417694330215454,
0.308513194... |
TASK DEFINITION: Given a document, generate a short title of the document. The title should convey the main idea/event/topic about which the document is being written. Note that URLs in the text have been replaced with [Link].
PROBLEM: In 1992 Clint Eastwoodâs âUnforgivenâ won four Academy Awards and sent his ... | Trump targets book threatens ex
| 8 | NIv2 | task418_persent_title_generation | fs_opt | [
0.2681393027305603,
0.5487829446792603,
-0.26458096504211426,
0.3160889148712158,
0.4769492745399475,
-0.06101121008396149,
0.42889297008514404,
0.7816131114959717,
-0.25336411595344543,
0.42116931080818176,
0.26790720224380493,
0.3176109790802002,
-0.40165603160858154,
-0.2415615022182464... |
You will be given a definition of a task first, then some input of the task.
In this task, you're given a question, a context passage, and four options which are terms from the passage. After reading a passage, you will get a brief understanding of the terms. Your job is to determine by searching and reading further in... | c | 1 | NIv2 | task231_iirc_link_classification | zs_opt | [
-0.03544720634818077,
0.5172401070594788,
-0.5537204742431641,
0.04062813147902489,
0.08956629037857056,
0.85682213306427,
0.7550450563430786,
0.838563084602356,
0.04494640976190567,
0.33328691124916077,
0.13757619261741638,
-0.08093631267547607,
-0.5191996097564697,
-0.4727407395839691,
... |
In this task, you need to write an incorrect answer to the given question. Along with the question, you are also given the correct answer(s) and the associated paragraph. An incorrect answer should be closely related to the content of the paragraph and/or the question but will not truthfully answer the question. Your i... | Abram Gannibal.
****
| 4 | NIv2 | task055_multirc_write_incorrect_answer | fs_opt | [
0.5076843500137329,
0.3193299174308777,
-0.629397988319397,
0.11971800029277802,
0.46075090765953064,
-0.8528861999511719,
0.6145455837249756,
0.5056498646736145,
0.10231417417526245,
-0.22954966127872467,
-0.2739117741584778,
0.23115704953670502,
-0.9703636765480042,
-0.05540809780359268,... |
You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Farsi.
[Q]: De igual modo, habría sorprendido que actuara bajo las órdenes de Marduk.
[A]: و به همان میزان ، او تعجب نمی کند که کورش تحت فرمانهای مردوک عمل میکند.
[Q]: Así, el primer componente constante del arrepentimiento es bá... | کتابها اغلب از منابع شگفت آوری می آمد.
| 5 | NIv2 | task1103_ted_translation_es_fa | fs_opt | [
0.2724543809890747,
0.15893509984016418,
-0.17404629290103912,
-0.37974512577056885,
-0.34683957695961,
-0.708388090133667,
1.5193363428115845,
0.2702524960041046,
0.7837917804718018,
0.13017776608467102,
-0.8587675094604492,
-0.7338317036628723,
-0.8528128266334534,
0.9500836133956909,
... |
Detailed Instructions: You are given a review about a place. You need to provide a rating from "1 star" to "5 stars" for this place.
Problem:With all of the restaurants to pick from in Las Vegas, we used the Yelp reviews to pick Picasso. We decided to sit outside since we had reservations on 7/4, just a little before ... | 5 stars | 8 | NIv2 | task1292_yelp_review_full_text_categorization | zs_opt | [
0.13151484727859497,
0.10078136622905731,
-0.4465908706188202,
0.5518790483474731,
0.18914783000946045,
-0.14979344606399536,
0.3553711771965027,
0.9847177863121033,
0.4263596832752228,
0.5416481494903564,
0.48357540369033813,
0.03857854753732681,
-0.3302701711654663,
0.4544892907142639,
... |
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.
One example: For a movie that gets no respect there sure are a lot of memorable quotes listed for this gem. Imagine a movie where Joe Piscopo is actually fun... | positive | 6 | NIv2 | task284_imdb_classification | fs_opt | [
0.11798956990242004,
0.2726091146469116,
-0.6342027187347412,
0.47289931774139404,
0.8669238090515137,
-0.2607504725456238,
1.3204851150512695,
1.0351755619049072,
-0.14016059041023254,
-0.010850762948393822,
-0.31152036786079407,
-0.012707512825727463,
-0.7556489706039429,
0.3677178919315... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
You 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... | ulcers | 0 | NIv2 | task306_jeopardy_answer_generation_double | fs_opt | [
-0.8181619644165039,
0.1410987377166748,
-0.06766392290592194,
0.19987913966178894,
-0.10385407507419586,
0.6611009836196899,
0.07965915650129318,
0.10655347257852554,
-0.2575717270374298,
-0.20750996470451355,
-0.2641259431838989,
-0.1309075653553009,
-0.14636929333209991,
-0.389568090438... |
You are given a sentence in Polish. Your job is to translate the Polish sentence into Hebrew.
Kawałek mnie inspiruje dramaturga lub pisarza lub naukowca, co z kolei może zainspirować lekarza lub dobroczyńcę lub opiekunkę do dziecka. | אז יצירה שלי עשויה לעורר השראה אצל מחזאי או סופר או מדען, וזה יהפוך לזרע שיעורר השראה אצל רופא או נדבן או בייבי-סיטר. | 0 | NIv2 | task1260_ted_translation_pl_he | zs_opt | [
-0.6516579389572144,
0.29024046659469604,
0.11931805312633514,
-0.3213527500629425,
-0.1784091293811798,
-0.4892914891242981,
0.7426249980926514,
-0.7273824214935303,
0.5861853957176208,
-0.6699241995811462,
0.1305100917816162,
0.4455433487892151,
-1.0990068912506104,
-0.002607320202514529... |
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... | Output: Yes
| 2 | NIv2 | task1196_atomic_classification_oeffect | fs_opt | [
0.6177203059196472,
0.27281826734542847,
0.07508336007595062,
-0.10528536885976791,
-0.3738170266151428,
-0.8170872926712036,
0.924839198589325,
0.8720865249633789,
-0.04254712164402008,
-0.4055960178375244,
-0.6793721914291382,
-0.15861937403678894,
-0.892112135887146,
0.06573806703090668... |
Definition: 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 wh... | Don's friend pulled Don's pants down in front of his graduating class. | 2 | NIv2 | task072_abductivenli_answer_generation | zs_opt | [
-0.03698359429836273,
0.5121882557868958,
0.06679084897041321,
-0.8037377595901489,
-0.27059680223464966,
0.19954241812229156,
0.6397160887718201,
0.39990389347076416,
0.26799309253692627,
-0.16995544731616974,
-0.8915114402770996,
0.4896303415298462,
-0.3663255572319031,
0.179096534848213... |
Instructions: In this task, you are given a hateful post in English from online platforms. You are expected to classify the post into two classes: aggresive or non-aggresive. An aggresive post is one that expresses feelings and opinions in an abusive way and tries to dominate others. Note that the URLs in the text have... | Non-aggresive | 3 | NIv2 | task335_hateeval_classification_aggresive_en | zs_opt | [
-1.146796464920044,
0.8114743828773499,
0.8433811068534851,
0.4031361937522888,
-0.01590418629348278,
-0.6543064117431641,
0.09764239192008972,
0.5761486291885376,
-0.2653283476829529,
0.7417011260986328,
0.05787268280982971,
-0.3022860884666443,
-0.5308570861816406,
-0.5052666664123535,
... |
Teacher:Given a sentence in French, generate a new French 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 o... | Les ordinateurs n'ont rien donné. | 6 | NIv2 | task406_mickey_fr_sentence_perturbation_generation | zs_opt | [
-0.10161386430263519,
0.2513812184333801,
-0.148717999458313,
-0.15741971135139465,
-0.02160307765007019,
-0.47543275356292725,
0.586088240146637,
0.43271294236183167,
0.26031458377838135,
-0.2122146487236023,
-0.9102922677993774,
-0.1013687402009964,
0.09258733689785004,
-0.58662098646163... |
Teacher:Given a trivia question, classify broad topical category from this list: 'theater', 'geology', 'book', 'tv', 'astronomy', 'aviation', 'military', 'government', 'boxing', 'projects', 'metropolitan_transit', 'law', 'venture_capital', 'broadcast', 'biology', 'people', 'influence', 'baseball', 'spaceflight', 'media... | location | 6 | NIv2 | task900_freebase_qa_category_classification | zs_opt | [
0.3647003769874573,
0.530146598815918,
-0.10082811117172241,
-0.06983371078968048,
0.38460594415664673,
-0.283599853515625,
0.47779905796051025,
0.39636945724487305,
-0.5827406048774719,
-0.013404651544988155,
0.01839412748813629,
0.11781005561351776,
-0.7908584475517273,
-0.18133527040481... |
Instructions: In this task, you are given a text from a social media post. Your task is to classify the given post into two categories: 1) yes if the given post is intentionally offensive, 2) no, otherwise. Also, generate label 'no' for offensive statements that appear to be unintentional, or non-offensive statements t... | No | 3 | NIv2 | task607_sbic_intentional_offense_binary_classification | zs_opt | [
-0.9738012552261353,
0.48530521988868713,
0.3341531455516815,
0.3546026051044464,
0.09013204276561737,
-0.19766899943351746,
0.43410825729370117,
0.11557980626821518,
0.09930288791656494,
0.689109206199646,
0.18715590238571167,
-0.23057185113430023,
-0.6184912323951721,
-0.3532160818576813... |
Detailed Instructions: You are given a sentence in English. Your job is to translate the English sentence into Galician.
Q: But there are endless problems with social gradients that are worse in more unequal countries — not just a little bit worse, but anything from twice as common to 10 times as common.
A: | Hai moitos que son peores nos países máis desiguais, non só un pouco peores senón moito máis frecuentes. | 9 | NIv2 | task1090_ted_translation_en_gl | zs_opt | [
-0.835502028465271,
0.9399036169052124,
0.15116950869560242,
-0.9914299249649048,
-0.2315230369567871,
-0.11096537113189697,
0.0789700374007225,
1.2392204999923706,
-0.9379807114601135,
0.006682048551738262,
-0.41988933086395264,
0.27998656034469604,
-1.1539641618728638,
0.2813600897789001... |
In this task the focus is on physical knowledge about the world. Given the provided goal task in the input, describe a process that would lead to the asked outcome. This process often involves physical motions with objects, such as moving them, arranging them in a certain way, mixing them, shaking them, etc.
One examp... | You'll need 100 #6 self-tapping screws. | 6 | NIv2 | task080_piqa_answer_generation | fs_opt | [
-0.18897472321987152,
0.9881848096847534,
-0.713288426399231,
0.2759467661380768,
-0.2787826657295227,
-0.049845319241285324,
0.14739316701889038,
0.4131351709365845,
0.007327212020754814,
0.18951228260993958,
-0.03740215301513672,
0.26958706974983215,
-0.2777714431285858,
0.13023068010807... |
Detailed Instructions: Given a sentence in Tagalog language, translate the sentence to English language keeping the meaning of the original sentence intact.
Q: Tagalog sentence: Matapos ang pagdating sa London siya ay naging isang pribadong tagapagturo ng matematika, pagbisita sa mga nag-aaral kanino siya at itinuro di... | After arriving in London he became a private tutor of mathematics, visiting the pupils whom he taught and also teaching in the coffee houses of London. | 9 | NIv2 | task451_opus_paracrawl_tl_en_translation | zs_opt | [
-0.17197009921073914,
0.6680724620819092,
-0.18323570489883423,
-1.461020827293396,
0.6648579835891724,
-0.9019708633422852,
0.592188835144043,
0.5157852172851562,
0.12077583372592926,
-0.30995112657546997,
0.2389170080423355,
0.39072898030281067,
-0.9399893879890442,
0.12466777116060257,
... |
TASK DEFINITION: In this task you will be given a list, of lists, of numbers. Each list is presented with brackets and comma-separated values. For example, a list of numbers is [1,2,3] and a list of two lists of numbers is [[1,2],[3,4,6]]. You should sum up the values at every position of every inner list and put it as... | [43, 184, -48, 88, 82, -60, 100, -73, 3]
| 8 | NIv2 | task122_conala_list_index_addition | fs_opt | [
0.3202444314956665,
-0.12091366201639175,
-0.7504984140396118,
-0.23966418206691742,
0.13890716433525085,
0.027214592322707176,
0.9483184814453125,
0.6109611988067627,
-0.3932458758354187,
-0.16087935864925385,
-0.524760365486145,
0.17793136835098267,
-0.6287089586257935,
0.063093252480030... |
Instructions: Given a part of privacy policy text, classify it into one of these categories:
(1) First Party Collection/Use (how and why a service provider collects user information),
(2) Third Party Sharing/Collection (how user information may be shared with or collected by third parties),
(3) User Choice/Contro... | User Choice/Control | 3 | NIv2 | task682_online_privacy_policy_text_classification | zs_opt | [
-0.4345366954803467,
0.36285829544067383,
-0.8384108543395996,
0.18525195121765137,
-0.45792269706726074,
-0.4197595417499542,
0.02316126599907875,
0.7500282526016235,
0.14210189878940582,
0.38125836849212646,
-0.35675671696662903,
-0.005011357367038727,
-0.12818622589111328,
-0.6025793552... |
You are given a password and you need to generate the number of steps required to convert the given password to a strong password. A password is considered strong if (a) it has at least 6 characters and at most 20 characters; (b) it contains at least one lowercase letter and one uppercase letter, and at least one digit... | 1
| 7 | NIv2 | task956_leetcode_420_strong_password_check | fs_opt | [
0.8986917734146118,
1.24220871925354,
0.2860839366912842,
-0.8288391828536987,
0.09470485895872116,
-0.04053337872028351,
1.6838650703430176,
-0.3161279261112213,
0.15748344361782074,
-0.7653384208679199,
0.12168814241886139,
-0.1458130180835724,
-1.09385347366333,
-0.40870967507362366,
... |
You will be given a definition of a task first, then some input of the task.
In this task, you need to answer the given multiple-choice question on the general math. Classify your answers into 'a', 'b', 'c', 'd', and 'e'.
Problem: the unit digit in the product ( 115 * 297 * 196 * 108 ) is :
Options: a ) 2 , b ) 7 , c... | d | 1 | NIv2 | task1420_mathqa_general | zs_opt | [
0.1517377346754074,
0.012478007934987545,
-0.7756789922714233,
-0.35919445753097534,
-0.20687335729599,
0.03083237260580063,
0.20130153000354767,
0.15147614479064941,
-0.7317806482315063,
0.15349175035953522,
-0.7823828458786011,
0.000407775747589767,
-0.052533313632011414,
-0.524499058723... |
Part 1. 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.
Part 2. Example
['q', '31', 'a', 'd', '53', '85', 'p', '77']
Answer: 1, 3, 5, 7, 8
Explanation: Here, the numbers in the list ar... | 1, 2, 3, 4, 6, 7, 8 | 7 | NIv2 | task637_extract_and_sort_unique_digits_in_a_list | fs_opt | [
-0.016289684921503067,
0.30009347200393677,
-0.5896733403205872,
-0.9098032712936401,
-0.013034326955676079,
0.616512656211853,
1.0275607109069824,
-0.23189321160316467,
-0.37021011114120483,
0.5631518959999084,
-0.6134703159332275,
-0.21810288727283478,
-0.6436325311660767,
-0.22470258176... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
You will be asked how to do a certain task. You should describe a physical process that does not lead to the asked outcome, yet it is closely related to it (i.e., it should use the words that are pro... | Place in empty trash bin. | 0 | NIv2 | task081_piqa_wrong_answer_generation | fs_opt | [
0.2523326575756073,
0.3173529803752899,
-1.074108600616455,
0.5486681461334229,
0.16098669171333313,
-0.6254981756210327,
0.7342658638954163,
1.0214016437530518,
-0.23930132389068604,
0.0696018785238266,
0.19468249380588531,
0.1658894419670105,
-0.18728193640708923,
-0.028808629140257835,
... |
Teacher: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.
Teacher: Now, understand the problem? Solve this instance: I am very dissapointed to... | Bad review | 6 | NIv2 | task929_products_reviews_classification | zs_opt | [
-0.7312847971916199,
-0.12116118520498276,
0.11495019495487213,
-0.3063971996307373,
0.5430877208709717,
-0.8687248229980469,
0.7411431670188904,
1.0359761714935303,
0.025074876844882965,
0.09520594775676727,
-0.03360561281442642,
0.10648684203624725,
-0.6350588798522949,
-0.46467578411102... |
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