inputs stringlengths 38 313k | targets stringlengths 0 4.86k | _template_idx int64 0 9 | _task_source stringclasses 1
value | _task_name stringlengths 19 85 | _template_type stringclasses 2
values | embedding listlengths 1.02k 1.02k |
|---|---|---|---|---|---|---|
Given a sentence in Somali language, translate the sentence to English language keeping the meaning of the original sentence intact
One example: Somali sentence: Lionel Messi waa ciyaaryahanka ugu weyn kubadda cagta abid
Solution is here: Lionel Messi is the greatest football player of all time
Explanation: The output ... | 13 Therefore their goods shall become a booty, and their houses a desolation: they shall also build houses, but not inhabit them; and they shall plant vineyards, but not drink the wine thereof. | 6 | NIv2 | task450_opus_paracrawl_so_en_translation | fs_opt | [
0.16770033538341522,
0.8892240524291992,
-0.6395115852355957,
-0.2545102834701538,
-0.0006298667285591364,
-0.9029861092567444,
-0.1476997435092926,
0.2944523096084595,
0.0639692097902298,
-0.07928960770368576,
0.04476191848516464,
1.1566680669784546,
-1.0161164999008179,
-0.18915559351444... |
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 a sentence in the Japanese and Filipino language. Your task is check if the Filipino sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise gene... | Yes | 0 | NIv2 | task1120_alt_ja_fil_answer_generation | fs_opt | [
0.43063974380493164,
-0.43639808893203735,
-0.6543206572532654,
0.26975566148757935,
0.17873486876487732,
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0.9799314737319946,
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-0.46241721510887146,
0.9443832635879517,
-0.33471423387527466,
0.96068489551544... |
You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Farsi.
One example: وقد كتبن اللغة وغالبا ما كانت لغة آلة وأحيانا شفرة ثنائية ترسل بعدها بالبريد لمركز البيانات لتنقل على شريط أو بطاقة ورقية مثقبة ثم تعاد الكرة مرة أخرى للتأكد.
Solution is here: و آنگاه آنها کُد می نوشتند ، معمولا ک... | من دولا میشم و لای پنجره رو باز میکنم. | 6 | NIv2 | task1108_ted_translation_ar_fa | fs_opt | [
-0.9038282632827759,
0.42233631014823914,
-0.6762055158615112,
-0.4635222554206848,
-0.36575260758399963,
-0.16997124254703522,
1.1601394414901733,
0.06653570383787155,
0.11681832373142242,
-0.21592476963996887,
-0.8744102120399475,
0.40009209513664246,
-0.49984949827194214,
0.495221853256... |
In this task, you will be presented with a question, and you have to write the part-of-speech tag for each word in the question. Here is the Alphabetical list of part-of-speech tags used in this task: CC: Coordinating conjunction, CD: Cardinal number, DT: Determiner, EX: Existential there, FW: Foreign word, IN: Preposi... | IN DT NNS IN NNP NNP IN NNP NNPS NNS IN NNP NNP NNP , NNP WDT NN VBD VBN RB . | 0 | NIv2 | task345_hybridqa_answer_generation | zs_opt | [
-0.3358423113822937,
0.5858023762702942,
-0.3185655176639557,
0.626926839351654,
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-0.7216027975082397,
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-0.17264237999916077,
0.27771979570388794,
-0.30876338481903076,
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In this task, you will be presented with a premise and a hypothesis sentence. Determine whether the hypothesis sentence entails (implies), contradicts (opposes), or is neutral with respect to the given premise sentence. Please answer with "Contradiction", "Neutral", or "Entailment".
Example: Premise: Lost Moon: The Per... | Solution: Contradiction | 5 | NIv2 | task1385_anli_r1_entailment | fs_opt | [
-0.01924598589539528,
0.7248507738113403,
0.03284512832760811,
-0.16718287765979767,
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-0.8647782802581787,
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-0.8916051387786865,
-0.16679179... |
Instructions: Given an entity, a before event, an after event, and an attribute related to the entity, generate a sentence as output. Your sentence should show the changes in the attribute of the entity.
Input: entity: tomatoes
before: in can
after: in pot
attr: location
Output: | location of tomatoes was in a can before and in pot afterwards | 3 | NIv2 | task1631_openpi_answer_generation | zs_opt | [
0.3832683861255646,
0.2683173418045044,
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0.7469444274902344,
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-0.5619775056838989,
0.9791765213012695,
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-0.2722799777984619,
0.2020166516304016,
0.30416709184646606,
-0.46222150325775146,
-0.39926543831825256,... |
This task is about classifying the similarity of two sentences. The sentences can be classified as (a) SIMILAR - similar to each other, and (b) DISSIMILAR - not similar to each other. Sentences that have the same RDF relationship in terms of [subject, predicate, object] are similar to each other. The input is a list of... | Solution: SIMILAR | 5 | NIv2 | task1408_dart_similarity_classification | fs_opt | [
-0.14408989250659943,
-0.13215945661067963,
-0.01497592031955719,
-0.019084973260760307,
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1.106360673904419,
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0.10431249439716339,
-0.9187491536140442,
-0.4030612111091614,
-0.44518178701400757,
0.211359947919... |
Detailed Instructions: In this task, you're shown a three-part story, with a beginning, middle, and ending. Your job is to slightly modify the middle part, so that the whole story becomes unlikely, improbable, or inconsistent. Generated sentences must minimally alter the given middle, with at most 4 new words added/exi... | Jason needed to cook. | 9 | NIv2 | task068_abductivenli_incorrect_answer_generation | zs_opt | [
0.4863552451133728,
0.557013988494873,
-0.16963903605937958,
-0.6956351399421692,
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-0.12309561669826508,
0.29008835554122925,
-0.5754762887954712,
-0.100264385342... |
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.
Example: sentence: i couldn't put the ... | Solution: the woman | 5 | NIv2 | task249_enhanced_wsc_pronoun_disambiguation | fs_opt | [
-0.35601696372032166,
0.6286261081695557,
0.11115439981222153,
0.02746628411114216,
0.11300407350063324,
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0.9869891405105591,
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-0.11317691951990128,
-0.39887815713882446,
0.13288818299770355,
-0.7193386554718018,
0.30849283933639526... |
You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Arabic.
Q: ¿Qué son los estados y los países?
A: | ولكن ماهي الدول والأمم ؟ | 4 | NIv2 | task1228_ted_translation_es_ar | zs_opt | [
0.3436204195022583,
0.4312293529510498,
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1.2164978981018066,
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-0.9022569060325623,
-0.046116121113300323,
-0.336556613445282,
-0.21205823123455048... |
Given the task definition and input, reply with output. You will be asked how to do a certain task. You should describe a physical process that does not lead to the asked outcome, yet it is closely related to it (i.e., it should use the words that are provided in the input). The physical process can be moving something... | Affix the loop-ended 4’ cords to the top of your poncho. Pound in stakes near to where the corners will be. If the stakes don’t hold, use a large rock. You will tie-off the cords to the stakes at the 1’-2’ position. Shove the handles of both trekking poles into the hood of the poncho, extend them as needed, and spike t... | 5 | NIv2 | task081_piqa_wrong_answer_generation | zs_opt | [
0.0622582770884037,
0.9481160044670105,
-0.21116316318511963,
0.6642248630523682,
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0.12272511422634125,
-0.48192939162254333,
0.1675213873386383,
-0.07439254224300385,
-0.3244172334671... |
In this task, You are given an amazon food product review and its summary. Your task is to Generate "True" if given review and its summary match, otherwise generate "False".
[Q]: 13 dollars for 24 cups free shipping over 50 dollars is the going rate. These folks are pulling a swiftie
Summary: Green Mountain Breakfas... | False
| 5 | NIv2 | task590_amazonfood_summary_correction_classification | fs_opt | [
-0.5003753900527954,
-0.5200574398040771,
0.4856749475002289,
-0.33265960216522217,
0.21856002509593964,
-1.0774158239364624,
-0.07131645083427429,
0.6350472569465637,
-0.043334320187568665,
0.12840765714645386,
-0.09896355867385864,
0.019459398463368416,
-0.6789964437484741,
0.00585500802... |
instruction:
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Arabic.
question:
ובכן, פיתרון אפשרי אחד של הפרדוקס של פרמי הוא, שכשחברה הופכת למתקדמת מספיק טכנולוגית כדי לחשוב על חיים בין הכוכבים, הם מאבדים את היכולת להבין כמה חשוב לשמור על כוכב הבית שלהם שהביא את ההתקדמות הזו מהתחלה... | نحن نعيش في بيئة معقدة: التعقيد والحيوية وكل الأنماط الواضحة في صور الأقمار الاصطناعية ، والفيديوهات.
| 9 | NIv2 | task1237_ted_translation_he_ar | fs_opt | [
-0.552900493144989,
0.2618084251880646,
0.051997411996126175,
-0.5994885563850403,
-0.4427386522293091,
0.01806151308119297,
0.7002230286598206,
0.12520727515220642,
0.3766685426235199,
-0.2524651885032654,
-1.0268070697784424,
0.1465226262807846,
-0.9171820878982544,
0.09220656752586365,
... |
Given a category and a set of five words, find the word from the set that does not belong (i.e. is the least relevant) with the other words in the category. Words are separated by commas.
Q: Category: kitchenware
Words: metal, glass, knifer, dish, cup
A: metal
****
Q: Category: military rank
Words: regular, major, ... | well
****
| 4 | NIv2 | task141_odd-man-out_classification_category | fs_opt | [
0.2342972457408905,
0.6419178247451782,
-0.40970104932785034,
-0.1734236776828766,
0.27334609627723694,
-0.16804072260856628,
-0.4110996425151825,
0.5581558346748352,
0.1175362765789032,
0.14910483360290527,
-0.09915105998516083,
-0.0825977474451065,
-0.6562042832374573,
0.0700182169675827... |
Part 1. Definition
The input is a tweet which can be Hate Speech or Offensive. Given such a tweet, output a phrase from the tweet that makes it hate speech or offensive. The output should contain only one such phrase. The output has to be from within the tweet itself. Do not generate words or phrases not present in the... | suck | 7 | NIv2 | task1504_hatexplain_answer_generation | fs_opt | [
-1.2777736186981201,
0.7422797679901123,
0.16057240962982178,
-0.035713016986846924,
-0.431255578994751,
-0.9117138385772705,
0.4373580813407898,
-0.03869553655385971,
0.6188567876815796,
0.21954822540283203,
-0.4473859965801239,
0.29746946692466736,
-0.7348626852035522,
-0.445855230093002... |
Instructions: You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Galician.
Input: No puedo querer ser apasionada a los 71 años.
Output: | Non chega querer ser apaixonada aos 71. | 3 | NIv2 | task1100_ted_translation_es_gl | zs_opt | [
-0.3754414916038513,
1.3778586387634277,
0.19756101071834564,
-1.4085919857025146,
-0.42904505133628845,
-1.2946206331253052,
-0.24035505950450897,
0.574777364730835,
0.10756733268499374,
-0.2984831929206848,
0.24499930441379547,
-0.25453492999076843,
-0.8671640157699585,
0.094836004078388... |
In this task, you're given a context, a sentence, and a character. The sentence describes an action or job of the given character. Also, the context provides more information about the sentence or the character. Your task is to return one of the emotions which are expressed by the Character in the given sentence. For ... | upset
| 0 | NIv2 | task293_storycommonsense_emotion_text_generation | fs_opt | [
0.39411991834640503,
0.4814680218696594,
-0.4196973741054535,
-0.25964415073394775,
-0.12555170059204102,
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0.5814347267150879,
0.6447701454162598,
-0.01859142817556858,
-0.06451761722564697,
0.1941668689250946,
-0.044120654463768005,
-0.42483967542648315,
-0.2344611734... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to determine if the two sentences clearly agree/disagree with each other, or if this can't be determined. Indicate your answer as yes or no respectively.
Q: Sentence 1: But researchers said that Americans are increasingly recognizing... | yes | 4 | NIv2 | task199_mnli_classification | zs_opt | [
-0.7405861020088196,
0.6217019557952881,
0.5775782465934753,
-0.0570409893989563,
0.23412857949733734,
-0.789601743221283,
0.49240249395370483,
1.003117322921753,
0.33645206689834595,
0.11503589153289795,
-0.44440901279449463,
-0.4632875621318817,
-0.3678935170173645,
-0.4835551679134369,
... |
In this task, you will be presented with a question in Persian. Based on the knowledge you need to answer the question, classify the question into "math_and_logic", "literature", or "common_knowledge".
انفال یا ثروتهای عمومی در اختیار کیست؟ | common_knowledge | 0 | NIv2 | task474_parsinlu_mc_classification | zs_opt | [
-0.9010052680969238,
1.213747501373291,
0.8446829319000244,
-0.4556984305381775,
-0.6943082809448242,
0.6275750398635864,
0.9323451519012451,
0.15078771114349365,
0.48196712136268616,
-0.6542768478393555,
-0.6954969167709351,
0.3559674918651581,
-0.9433942437171936,
-0.017088472843170166,
... |
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing reservation, `... | no_reservation | 0 | NIv2 | task573_air_dialogue_classification | zs_opt | [
-0.0032610741909593344,
-0.10877908766269684,
-0.3691392242908478,
-0.655197262763977,
0.4238576591014862,
-0.31208106875419617,
0.9648181200027466,
0.5300090312957764,
0.20251893997192383,
0.20018942654132843,
0.43881165981292725,
-0.4443069100379944,
-0.5952567458152771,
-0.1377755403518... |
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 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, see... | शिकागो विश्वविद्यालय में 1998 के बाद से इसके मामलों में 25 गुना की वृद्धि हुई है। | 2 | NIv2 | task432_alt_en_hi_translation | fs_opt | [
0.044371169060468674,
0.8003875613212585,
-0.21797285974025726,
0.39149928092956543,
-0.13496071100234985,
-0.7895743250846863,
0.0372229740023613,
0.6718538999557495,
-0.06054088845849037,
-0.3640110492706299,
-0.299059122800827,
0.4770665168762207,
-0.09822045266628265,
0.250968277454376... |
Q: You need to create a question containing a blank (_), based on the given context word. Your question must contain two persons --PersonX and PersonY. The expected answer to your question must be PersonX. PersonX and PersonY should not be equally likely to fill the blank. There should be an agreed upon answer to fill ... | PersonX came limping into work but not PersonY because _ had worked out too hard. | 7 | NIv2 | task032_winogrande_question_generation_person | zs_opt | [
0.11014630645513535,
1.0083510875701904,
-0.07878221571445465,
-0.18725267052650452,
-0.046783871948719025,
-0.3452489376068115,
0.9330560564994812,
0.4276953935623169,
-0.18383672833442688,
-0.8979119062423706,
-0.11398624628782272,
-0.18941839039325714,
-0.4203743636608124,
0.43696692585... |
In this task, you are given a sentence in either Spanish or English. Your task is to determine the language of the input sentence. Input sentences can only be in Spanish or English, and they cannot be in two languages at the same time.
Let me give you an example: All of us here are pleased that the courts have acqui... | English | 8 | NIv2 | task533_europarl_es-en_language_identification | fs_opt | [
-0.16057099401950836,
0.6590213179588318,
0.9213935136795044,
-0.43035775423049927,
0.35502588748931885,
-0.8360499739646912,
-0.3033878207206726,
1.1219995021820068,
0.5658251047134399,
-0.40314897894859314,
-0.2670905590057373,
0.07600869983434677,
-0.21108447015285492,
-0.82595229148864... |
Categorize the comment on the basis of threat. If the comment is threatening output Yes, otherwise output No.
Input: Consider Input: Human lab rat 75 year old male on new protocol over 13 years has mental acuity he had in is thirties.
tinyurl.com/nl9nq2y http://tinyurl.com/os6vsvl
Output: Yes
Input: Consider Input... | Output: Yes
| 2 | NIv2 | task1722_civil_comments_threat_classification | fs_opt | [
-0.20219916105270386,
0.23388874530792236,
-0.08122942596673965,
0.4288268983364105,
-0.019142137840390205,
-0.8001842498779297,
-0.11466987431049347,
0.6658787727355957,
0.6174393892288208,
0.5693587064743042,
-0.25025424361228943,
0.42797309160232544,
0.06720062345266342,
-0.238586053252... |
In this task, you will be shown a Persian passage and a question, and you have to determine whether the question is answerable based on the passage or not. If the question is answerable, choose the "True" label, and if not select "False"
One example: فتوسنتز فرایندی زیستشیمیایی است که در آن، انرژی نورانی خورشید توسط گ... | True | 6 | NIv2 | task396_persianqa_classification | fs_opt | [
0.1834404319524765,
0.5144913196563721,
-0.4603101313114166,
0.077217698097229,
-0.18298457562923431,
-0.3709726929664612,
0.8562605381011963,
0.6837639808654785,
-0.16335023939609528,
0.4346684217453003,
-0.7853313088417053,
0.5359145998954773,
-0.4948321580886841,
0.6292407512664795,
0... |
Detailed Instructions: 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.
Q: Tweet: @GoHard_Brown @your_daddy9 & xavier you bitch.
Label:... | false | 9 | NIv2 | task905_hate_speech_offensive_classification | zs_opt | [
-1.1707020998001099,
0.35318446159362793,
0.6746491193771362,
0.4986623525619507,
-0.5387438535690308,
-1.343071460723877,
0.658625602722168,
0.32675057649612427,
0.7690971493721008,
0.14760950207710266,
-0.1103353351354599,
-0.6623307466506958,
-0.7199510931968689,
-0.9016558527946472,
... |
instruction:
From the given sentence, extract the phrase (often noun or verb) that carries the given relationship. The generated phrase should be present in the sentence.
question:
Given Relationship: 'be part of', Sentence: 'So it comes as no surprise that Russia was part of Europe .'
answer:
part
question:
Given Re... | consists
| 9 | NIv2 | task678_ollie_actual_relationship_answer_generation | fs_opt | [
0.43312525749206543,
0.8709020614624023,
-0.003272551577538252,
-0.42635631561279297,
0.006457989104092121,
0.2565425634384155,
0.4217165410518646,
0.7110112905502319,
0.2408370077610016,
0.03684847801923752,
-0.13082683086395264,
0.2406926304101944,
-0.411202609539032,
0.8339259624481201,... |
Detailed Instructions: The input is a tweet which can be Hate Speech or Offensive. Given such a tweet, output a phrase from the tweet that makes it hate speech or offensive. The output should contain only one such phrase. The output has to be from within the tweet itself. Do not generate words or phrases not present in... | ugly fuckin nigger | 8 | NIv2 | task1504_hatexplain_answer_generation | zs_opt | [
-1.0133247375488281,
0.8327436447143555,
0.3303253650665283,
0.698458731174469,
-0.5291501879692078,
-0.8263075351715088,
-0.40727099776268005,
0.896957516670227,
0.3742516040802002,
0.3132634460926056,
-0.4216647148132324,
-0.037581175565719604,
-0.30671942234039307,
-0.7110323905944824,
... |
In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determ... | No
****
| 4 | NIv2 | task1200_atomic_classification_xeffect | fs_opt | [
0.49672549962997437,
0.33016854524612427,
0.2589152455329895,
-0.45661717653274536,
-0.688870370388031,
-0.4845861494541168,
1.4301657676696777,
0.6779996752738953,
-0.41731977462768555,
-0.33769094944000244,
-0.6090303659439087,
-0.31336045265197754,
-0.741982638835907,
0.1147041171789169... |
You are given a sentence in Galician. Your job is to translate the Galician sentence into Italian.
Example: Isto inclúe un sistema en árabe chamado al-jebra.
Example solution: Tra di esse, si annovera il piccolo sistema in arabo detto al-jebr.
Example explanation: The Galician sentence is correctly translated into Ital... | Solution: E ciò che collega la catena montuosa alla pianura costiera è una zona chiamata Shephelah, che è una serie di valli e di creste che si sviluppano da est a ovest, e si può seguire lo Shephelah, attraversarlo per andare dalle montagne alla pianura costiera. | 5 | NIv2 | task1243_ted_translation_gl_it | fs_opt | [
-0.08869779855012894,
0.9461935758590698,
-0.29535162448883057,
-0.14119237661361694,
-0.4374079704284668,
-0.9601085782051086,
0.7530438899993896,
0.715160608291626,
-1.199946403503418,
-0.040850795805454254,
-0.5282272100448608,
-0.25820091366767883,
-0.9717700481414795,
0.54351663589477... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Galician. Your job is to translate the Galician sentence into Spanish.
En realidade, o que estamos intentando é tomar un polo, modificalo, e facer o "" polosaurus "".
Output: | En realidad estamos tratando de tomar un pollo, modificarlo, y hacer el « pollosaurus » | 1 | NIv2 | task1240_ted_translation_gl_es | zs_opt | [
-0.8986986875534058,
1.1081937551498413,
-0.2259807586669922,
-0.5786563158035278,
-0.544943630695343,
-0.8909945487976074,
-0.4690031409263611,
0.9977381825447083,
-0.1268400102853775,
-0.0679231584072113,
-0.21279111504554749,
-0.3111414909362793,
-0.435519814491272,
0.010932103730738163... |
Detailed Instructions: In this task, you will be given two sentences separated by "because". You should decide whether the first sentence can be the result of the second sentence. If you can see a possible cause and effect relationship, answer with "plausible", otherwise answer with "not plausible".
Q: the father shut ... | not plausible | 9 | NIv2 | task392_inverse_causal_relationship | zs_opt | [
-0.7149220705032349,
0.6645117998123169,
0.6892442107200623,
-0.7620606422424316,
-0.4577729105949402,
0.20206399261951447,
0.7973313331604004,
1.10355806350708,
0.386573851108551,
-0.11936090886592865,
-0.45933014154434204,
0.4628070592880249,
-0.6930015683174133,
-0.4265315532684326,
-... |
Definition: 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 ha... | Yes | 2 | NIv2 | task1206_atomic_classification_isbefore | zs_opt | [
0.5087134838104248,
0.24710136651992798,
0.0975828692317009,
0.19063755869865417,
-0.4945167899131775,
-0.6951959133148193,
1.2652325630187988,
0.38916873931884766,
-0.4131610095500946,
-0.6225638389587402,
-0.49931973218917847,
-0.10693609714508057,
-0.3660581111907959,
0.3267918229103088... |
Q: Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it ... | Sie werden wahrscheinlich eine Substanz in jemandes Wein beschuldigen. | 7 | NIv2 | task416_mickey_de_sentence_perturbation_generation | zs_opt | [
-0.4800860285758972,
0.7566252946853638,
-0.14177672564983368,
0.02808806486427784,
0.0905923992395401,
-0.19360403716564178,
0.8182961940765381,
0.9095325469970703,
0.22623971104621887,
-0.4389854073524475,
-0.41289258003234863,
0.46550607681274414,
-0.9299110174179077,
0.1122839674353599... |
A text is given in Hindi. Translate it from the Hindi language to the Oriya language. The translation must not omit or add information to the original sentence.
कल मैंने आप सबों से अनुरोध किया था कि आप पूर्वोत्तर यात्रा से जुड़ी अपनी तस्वीरें इंस्टाग्राम MagniicentNortheast पर साझा करें।
ସେ ପଚାରିଛନ୍ତି, “ଉତ୍ତର-ପୂର୍ବାଞ୍... | 2016 ସୁଦ୍ଧା 121 କ୍ୟାଟ୍ରିଜ୍ ଆଧାରିତ ନିଉକ୍ଲିକ୍ ଏସିଡ ଏମ୍ପ୍ଲିଫିକେସନ୍ ଟେଷ୍ଟ (ସିବିଏନ୍ଏଏଟି) ମେସିନ୍ ଥିଲା ।
| 0 | NIv2 | task985_pib_translation_hindi_oriya | fs_opt | [
-0.9495811462402344,
-0.3788960874080658,
-0.3499612510204315,
0.2748006284236908,
-0.11126729846000671,
-0.024271558970212936,
-0.0025706684682518244,
0.22949716448783875,
-0.6689409613609314,
-0.03319266438484192,
-0.5632820725440979,
-0.5489020347595215,
-0.3251841366291046,
0.062543615... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
1つはその情報を処理して周りの環境を理解することここに車線がありあそこに障害物があると把握しそれをドライバーに伝えます
Output: | Unha, e primeiro de todo, procesa a información para comprender o entorno: estas son as liñas dos carrís, estes son os obstáculos; e despois comunícalle esta información ao condutor. | 1 | NIv2 | task1095_ted_translation_ja_gl | zs_opt | [
-0.4966745972633362,
-0.04151211678981781,
0.45633208751678467,
-0.4562748670578003,
-0.09927549213171005,
-0.5381585359573364,
0.004836725071072578,
0.6490060091018677,
0.06657566130161285,
0.0452679879963398,
-0.9182377457618713,
-0.5530709028244019,
-0.14865170419216156,
0.1257598698139... |
Teacher:You are given a short paragraph, a question and two choices to answer from. Choose the correct answer based on the paragraph and write the answer(not the key).
Teacher: Now, understand the problem? Solve this instance: Paragraph: The more tightly packed the particles inside the material are, the more dense we s... | decreases | 6 | NIv2 | task1731_quartz_question_answering | zs_opt | [
-0.06740831583738327,
0.467672735452652,
0.02695801854133606,
0.018303068354725838,
-0.6992855668067932,
-0.5944604873657227,
0.09453145414590836,
1.1357589960098267,
0.1913202852010727,
0.21041539311408997,
-0.5318096876144409,
-0.21840864419937134,
-0.42370128631591797,
-0.46257698535919... |
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 'informal'... | formal | 4 | NIv2 | task1533_daily_dialog_formal_classification | zs_opt | [
-0.7479835152626038,
0.6611673831939697,
0.14895403385162354,
-0.6722350120544434,
-0.5179022550582886,
-0.2837042212486267,
1.2524306774139404,
-0.3827611804008484,
0.286933034658432,
-0.3888622522354126,
-0.17405204474925995,
-0.5775722861289978,
-0.6719902753829956,
0.7289424538612366,
... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
全て肋骨の間から行うのです
Solution: Wszystko jest robione pomiędzy żebrami.
Why? The Japanese sentence is correc... | Gdybyście jednak zobaczyli taką protokomórkę, nie pomylilibyście jej z czymkolwiek żywym. | 0 | NIv2 | task1097_ted_translation_ja_pl | fs_opt | [
0.3970782160758972,
0.5846797227859497,
0.10331210494041443,
-0.15440908074378967,
-0.009238125756382942,
0.32328343391418457,
1.288927674293518,
-0.19757862389087677,
-0.10933046042919159,
-0.40218499302864075,
0.06831029802560806,
0.2768231928348541,
-0.4090116024017334,
0.85129410028457... |
Given the task definition and input, reply with output. In this task, you're given a question, along with a context passage which has extra information available on certain terms mentioned in it, i.e., the proper nouns in the passage. Your job is to determine whether information from more than one term is needed to ans... | b | 5 | NIv2 | task232_iirc_link_number_classification | zs_opt | [
0.9842925071716309,
-0.041812457144260406,
-0.809781014919281,
0.7207337617874146,
0.23562325537204742,
-0.10817749798297882,
0.29020416736602783,
0.798987090587616,
-0.3697986602783203,
-0.4022313952445984,
-0.30270689725875854,
0.43230241537094116,
-0.2511861026287079,
0.1005325913429260... |
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 | task1200_atomic_classification_xeffect | zs_opt | [
0.2775806784629822,
0.3040235936641693,
0.48406654596328735,
-0.3935684859752655,
-0.3811589479446411,
-0.7508473992347717,
1.2515003681182861,
0.5611525177955627,
-0.7738566398620605,
-0.4019770622253418,
-0.27669888734817505,
-0.7040232419967651,
-0.4138408899307251,
0.2592913508415222,
... |
In this task, you are given a sentence which is either in the Hindi language or English language. You task is to identify the language of input sentence. Input sentence can be in Hindi or English language only and also it cannot have two languages at a time.
Q: The BJP has split the state into six regions , each to be ... | English | 4 | NIv2 | task427_hindienglish_corpora_hi-en_language_identification | zs_opt | [
0.07953858375549316,
-0.020353585481643677,
0.591113805770874,
0.047859419137239456,
-0.04453297704458237,
-0.6312504410743713,
0.2689133286476135,
-0.28029710054397583,
0.12611934542655945,
-0.4968219995498657,
-0.5308619737625122,
0.033163487911224365,
0.5317554473876953,
0.4751070141792... |
In this task, you're given a dialogue between a customer and a flight booking agent with a gap in the conversation. Your job is to find the answer of the previous dialogue. Avoid using irrelevant extra information while creating the answer. The answer should be relevant to the question before the blank. If you fill the... | Solution: customer: I want to travel in business class flight. | 5 | NIv2 | task574_air_dialogue_sentence_generation | fs_opt | [
0.19521193206310272,
0.1525881290435791,
-0.6669405698776245,
-0.8346779346466064,
0.3354702889919281,
-0.3639192283153534,
1.6921507120132446,
-0.16641709208488464,
-0.49419811367988586,
0.08410434424877167,
0.09856370091438293,
-0.5113334059715271,
-0.7004424333572388,
0.830052375793457,... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task you are expected to fix an SQL query based on feedback. You will be given an SQL statement and an English description with what is wrong about that SQL statement. You must correct the SQ... | SELECT T1.Season , T1.Player , T2.Name FROM match_season AS T1 JOIN team AS T2 ON T1.Team = T2.Team_id | 0 | NIv2 | task076_splash_correcting_sql_mistake | fs_opt | [
0.5063987970352173,
0.7056905031204224,
-1.326690912246704,
0.8369894027709961,
-0.26944369077682495,
-0.6142627596855164,
0.7340799570083618,
0.7699260115623474,
-0.31442978978157043,
0.004933391697704792,
0.13884377479553223,
0.3537991940975189,
-0.22688142955303192,
0.5470244884490967,
... |
Detailed Instructions: In this task, you need to Translate Czech text to English.
Q: Předmětem řešení je zařízení na regulaci dtoby tuhnutí voskových modelů pro přesné lití, kde nosiče formy jsou opatřeny vyjímatelnou otevírací kladkou, přičemž pod otevírací lištou automatického otevírání forem je uspořádán dvojči... | The subject of the solution is a control device dakoby solidification wax models for accurate casting, wherein the mold carriers are provided with removable opening pulley with under opening mold for automatic opening of molds a double-acting pressure cylinder is provided with an opening piston rod, coupled with ... | 9 | NIv2 | task842_para_pdt_cs_en_translation | zs_opt | [
-0.22644256055355072,
0.24426816403865814,
-0.5281982421875,
-0.17249950766563416,
-0.007734628859907389,
-0.8925732374191284,
0.0632438138127327,
0.902185320854187,
0.16615939140319824,
0.6718301773071289,
-0.11253051459789276,
-0.05063216760754585,
0.319784939289093,
0.1635153591632843,
... |
Detailed Instructions: You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Japanese.
See one example below:
Problem: A ideia é muito, muito simples.
Solution: このアイデアはとてもシンプルで
Explanation: The Portugese sentence is correctly translated into Japanese, because the meaning is prese... | 多くの場合これは有効です | 4 | NIv2 | task1275_ted_translation_pt_ja | fs_opt | [
-0.4484145939350128,
0.6159604787826538,
0.04008014500141144,
-0.5768559575080872,
-0.10939192771911621,
-1.1088719367980957,
0.4659106433391571,
0.4103964865207672,
0.5621335506439209,
-0.45999079942703247,
-0.8464385271072388,
-0.026177797466516495,
-0.8804794549942017,
0.435057222843170... |
The input is a conversation between an automated system and a user looking for suggestions for pubs, restaurants and coffee shops in Cambridge. In the dialogue, the user may provide some criteria for the type of place they want such as price range, cuisine, etc. Similarly, the user may ask details of the place suggeste... | You are looking for an international restaurant. You don't care about the price range. Make sure you get the phone number and price.
| 3 | NIv2 | task1499_dstc3_summarization | fs_opt | [
0.6645207405090332,
0.3958504796028137,
-0.3231472969055176,
-0.38722193241119385,
0.4316994547843933,
-0.46917372941970825,
0.5299725532531738,
0.8148455023765564,
-0.5676889419555664,
0.016937751322984695,
0.5009927749633789,
0.026572199538350105,
-0.4948340058326721,
0.117274209856987,
... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Sentence 2 contradicts sentence 1. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to c... | Men are hacking their way through a jungle landscape
| 6 | NIv2 | task185_snli_contradiction_to_neutral_text_modification | fs_opt | [
-0.009597007185220718,
-0.16499629616737366,
-0.8108564615249634,
-0.27478915452957153,
0.08496057987213135,
-0.5183529853820801,
0.14947088062763214,
1.1098549365997314,
0.35098910331726074,
-0.587261438369751,
-0.85615074634552,
-0.29132845997810364,
-0.25240349769592285,
-0.236225873231... |
TASK DEFINITION: Given a sentence in English language, translate the sentence to Igbo language keeping the meaning of the original sentence intact
PROBLEM: English sentence: Deuteronomy 16 1 Observe the month of Abib, and keep the passover unto the LORD thy God: for in the month of Abib the LORD thy God brought thee fo... | Jizọs Kraịst—Mezaịa ahụ E Kwere ná Nkwa
| 8 | NIv2 | task452_opus_paracrawl_en_ig_translation | fs_opt | [
0.10700946301221848,
-0.13916653394699097,
-0.4467158317565918,
-0.06957601010799408,
-0.3082612156867981,
-0.7354352474212646,
0.5063103437423706,
0.24341273307800293,
-0.21037933230400085,
-0.04170539975166321,
-0.7486298084259033,
0.5267883539199829,
-1.0307750701904297,
-0.026625744998... |
In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determ... | No
| 5 | NIv2 | task1211_atomic_classification_hassubevent | fs_opt | [
0.22264668345451355,
0.2922378182411194,
0.4851086437702179,
-0.374929815530777,
-0.6259686946868896,
-0.5611273050308228,
1.394883632659912,
0.456367164850235,
-0.6035980582237244,
-0.5613282322883606,
-0.4137381911277771,
-0.6963031888008118,
-0.8894779682159424,
0.3600175976753235,
1.... |
Instructions: In this task, you are given a context tweet, a question and corresponding answer of given question. Your task is to classify this question-answer pair into two categories: (1) "yes" if the given answer is right for question, and (2) "no" if the given answer is wrong for question.
Input: Context: Bill Plun... | yes | 3 | NIv2 | task241_tweetqa_classification | zs_opt | [
-0.971110463142395,
-0.14017823338508606,
-0.11486679315567017,
0.19618387520313263,
-0.4122250974178314,
0.011052006855607033,
0.6088722944259644,
0.21363672614097595,
0.3439302444458008,
0.04598112404346466,
0.3373754024505615,
0.2604380249977112,
0.20524962246418,
-0.07979746907949448,
... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Italian. Your job is to translate the Italian sentence into English.
Ma in qualche modo ciò che colpisce l'immaginazione di chiunque, o l'immaginazione di molti... in qualche modo dal Big Bang si è prodotto questo ... | But somehow what strikes everybody's imagination — or lots of people's imagination — somehow from that original Big Bang we have this beautiful world that we live in today. | 1 | NIv2 | task1247_ted_translation_it_en | zs_opt | [
0.004617008846253157,
1.180589199066162,
0.4104682207107544,
-0.17268827557563782,
-0.20689307153224945,
-0.7680392265319824,
0.040133338421583176,
0.7504628896713257,
0.06309039145708084,
-0.17613784968852997,
-0.44881853461265564,
0.3025285601615906,
-0.6492844820022583,
0.11086526513099... |
Detailed Instructions: In this task, you're given an article and an answer. Your task is to generate the question for the answer based on the given article.
Problem:Article: While waiting to pick up a friend at an airport in Portland, Oregon, I had one of those lifechanging experiences that you hear other people talk a... | Which word could best describe the baby girl? | 8 | NIv2 | task311_race_question_generation | zs_opt | [
0.7634531259536743,
0.688957929611206,
-0.6812862753868103,
-0.39055830240249634,
0.32076913118362427,
0.025178812444210052,
1.1523277759552002,
0.5121985673904419,
0.3673788905143738,
-0.23480254411697388,
-0.7307759523391724,
0.8422302007675171,
-0.5343017578125,
0.22366231679916382,
-... |
You will be given a definition of a task first, then some input of the task.
In this task, you need to generate an appropriate title for the given summary of some paragraph. The generated title must be short and should include the main topic of the given text. Your summary should be less than 20 words long.
Tension be... | Turkey failed coup: How do Turks in Europe see Erdogan? | 1 | NIv2 | task1358_xlsum_title_generation | zs_opt | [
-0.2272637039422989,
1.0064373016357422,
0.2222653031349182,
-0.11227913945913315,
-0.02644069865345955,
-0.42006659507751465,
0.9064597487449646,
0.10454922914505005,
-0.11078359931707382,
0.5417938232421875,
-0.04185095429420471,
0.479148268699646,
-0.7288538217544556,
0.1411033570766449... |
In this task, you're given an article, a question which often contains a blank and four options (associated with "A", "B", "C", "D"). Your task is to find the correct answer (from the given options) for the question from the given article and return one of the options from "A", "B", "C", and "D". Do not generate anythi... | B
| 3 | NIv2 | task309_race_answer_generation | fs_opt | [
0.5104188323020935,
0.5006788969039917,
-0.45061159133911133,
0.07891914248466492,
0.23294973373413086,
-0.03137369453907013,
0.033181484788656235,
0.7152389883995056,
0.06914307177066803,
0.3113080561161041,
0.32374104857444763,
0.28701531887054443,
-0.6570819616317749,
0.2228733003139495... |
Instructions: In this subtask, you will answer a simple science question. Please indicate the correct answer. If you're not sure about the answer, choose the last option "I don't know". Do not generate anything else apart from one of the following characters: 'A', 'B, 'C', 'D', 'E'. The "A"-"D" responses correspond to ... | A. | 3 | NIv2 | task047_miscellaneous_answering_science_questions | zs_opt | [
0.4360637068748474,
0.7517714500427246,
-0.4479488730430603,
-0.2766440510749817,
0.020602362230420113,
-1.4813998937606812,
0.8276316523551941,
0.5754643678665161,
-0.14720512926578522,
0.1740574836730957,
-0.20753993093967438,
-0.6812646389007568,
-0.596298098564148,
-0.8086476922035217,... |
In this task, you're given a short story of five sentences written in natural language. However, the order of the given story is not correct. Your job is to return the correct order for the given five sentences to create a coherent short story with the new order that has the correct flow. Generate your answer using the... | 21543
| 5 | NIv2 | task300_storycloze_order_generation | fs_opt | [
0.3949928879737854,
0.4539533257484436,
-0.6773927211761475,
-0.10674969851970673,
-0.32298314571380615,
-1.1818346977233887,
0.5153471231460571,
0.6327530145645142,
-0.15474644303321838,
0.00225130096077919,
-0.7197113037109375,
-0.07120020687580109,
-0.9450693130493164,
0.083129592239856... |
You will be given a definition of a task first, then some input of the task.
This task is about translating a given English language sentence to Yoruba language.
Keep your eyes on my face, and keep your eyes on my cheeks; one keeps one's eyes on the person with whom one goes visiting.
Output: | Wò mí lójú, wò mí lẹ́ẹ̀kẹ́; ẹni a bá lọ sóde là ń wò lójú. | 1 | NIv2 | task1685_menyo20k_translation | zs_opt | [
0.9673356413841248,
0.8273295164108276,
0.3254713714122772,
-0.15791882574558258,
0.020767919719219208,
-0.11218410730361938,
0.34647849202156067,
0.007789122872054577,
0.6183843612670898,
-0.557794451713562,
0.5351983308792114,
0.01387416198849678,
-0.6591471433639526,
0.35049670934677124... |
This task is about identifying the object of a given sentence. The object of a sentence is the person or thing that receives the action of the verb. It is the who or what that the subject does something to. Each sentence in this task is guaranteed to contain a single object. The input is a sentence and the output is th... | Manuel Valls | 4 | NIv2 | task1413_dart_object_identification | zs_opt | [
-0.8170558214187622,
0.6543997526168823,
-0.1384648084640503,
-0.394477903842926,
-0.5378480553627014,
-0.13592791557312012,
1.39892578125,
0.28758352994918823,
0.31346428394317627,
-0.1331087201833725,
-1.3097350597381592,
-0.38278788328170776,
-0.06580807268619537,
0.3232795298099518,
... |
TASK DEFINITION: In this task, you will be presented with a text and a pronoun. You should write the name that the pronoun refers to. Position of the pronoun in the text is showed within two "_"s.
PROBLEM: Justin O'Mara Brown (born April 16, 1982 in Fletcher, Oklahoma) is a former professional American, Canadian footba... | Catherine Ann Jones
| 8 | NIv2 | task330_gap_answer_generation | fs_opt | [
0.08426050841808319,
0.21665434539318085,
-0.6623027920722961,
0.5860180854797363,
-0.4491463899612427,
-0.12560202181339264,
0.0076752519235014915,
0.289347767829895,
0.21404676139354706,
0.051814012229442596,
-0.47050729393959045,
0.6219228506088257,
-0.6749869585037231,
-0.0300395712256... |
Instructions: You are given a sentence in Galician. Your job is to translate the Galician sentence into Arabic.
Input: Fixemos todos estes descubrimentos en laboratorios espallados polo mundo.
Output: | لقد حققنا كل هذه الاكتشافات المتلاحقة من مختبرات في جميع أنحاء العالم. | 3 | NIv2 | task1241_ted_translation_gl_ar | zs_opt | [
-0.028677066788077354,
0.48751533031463623,
-0.34034502506256104,
-0.5794992446899414,
-0.6573867797851562,
-0.2923888862133026,
-0.01349226851016283,
0.030621875077486038,
0.23187865316867828,
-0.2303651124238968,
-0.7782326936721802,
0.38346564769744873,
-0.41427499055862427,
0.584750771... |
Given the task definition, example input & output, solve the new input case.
In this task, you will be presented with a premise and a hypothesis sentence. Determine whether the hypothesis sentence entails (implies), contradicts (opposes), or is neutral with respect to the given premise sentence. Please answer with "Con... | Contradiction | 1 | NIv2 | task1385_anli_r1_entailment | fs_opt | [
-0.24019746482372284,
0.6991989612579346,
-0.6356557011604309,
0.6660974025726318,
0.11813085526227951,
0.20147556066513062,
0.3024720251560211,
0.5221790671348572,
0.3423588275909424,
-0.3718785345554352,
-0.8692216873168945,
0.3536234200000763,
-0.15797922015190125,
-0.07156853377819061,... |
Instructions: In this task, you are given an input list A. You need to convert all the alphabets in the list with a number representing their position in the English alphabet. E.g., replace A by 1, B by 2, a by 1, b by 2, and so on.
Input: ['G', 'r', 'f', 'e', 'F', 'z', '6653', 'n', '4305']
Output: | 7, 18, 6, 5, 6, 26, 6653, 14, 4305 | 3 | NIv2 | task622_replace_alphabets_in_a_list_by_their_position_in_english_alphabet | zs_opt | [
-0.42814433574676514,
-0.17876389622688293,
0.7716065049171448,
-0.5872457027435303,
0.33542898297309875,
-0.83427494764328,
-0.16339410841464996,
-0.18340221047401428,
-0.17997224628925323,
-0.23306085169315338,
-0.43779879808425903,
-0.3008573055267334,
-0.36228567361831665,
-0.805248141... |
Detailed Instructions: In this task, you are given text for US Congressional and California state bills, your task is to generate a summary for this bill.
Q: SECTION 1. ESTABLISHMENT OF NONDEDUCTIBLE TAX-FREE INDIVIDUAL
RETIREMENT ACCOUNTS.
(a) In General.--Subpart A of part I of subchapter D of cha... | Amends the Internal Revenue Code to establish special individual retirement accounts that are nondeductible. Makes such accounts nontaxable if earnings on contributions are held for at least five years. Applies the early withdrawal penalty to distributions made before the end of the five year-period. | 9 | NIv2 | task1658_billsum_summarization | zs_opt | [
1.011566162109375,
-0.17277345061302185,
-0.6126163601875305,
0.18152201175689697,
0.5680133104324341,
-0.33577847480773926,
1.1651840209960938,
0.9837616086006165,
-0.020907193422317505,
0.2619865834712982,
0.27130240201950073,
-0.04820902273058891,
-0.3149532973766327,
0.5969260931015015... |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Galician.
[EX Q]: האם אנו צריכים לאכול אוכל אורגני, או שאנו צריכים לאכול טופו?
[EX A]: Debemos comer carne orgánica ou debemos comer tofu?
[EX Q]: והוא נותן סימן כניסה לחלילן באופן כזה.
[EX A]: E sinala a un flautista así.
[EX Q]: ... | E isto é — esencialmente, este tipo de remix creativo é un selo distintivo da innovación.
| 6 | NIv2 | task1110_ted_translation_he_gl | fs_opt | [
-1.3002123832702637,
0.6618059277534485,
0.14087527990341187,
0.24634777009487152,
-0.40553051233291626,
-0.5991802215576172,
-0.0323784165084362,
0.3650733232498169,
0.15126270055770874,
-0.2776241898536682,
0.2687028646469116,
0.19112437963485718,
-0.8521393537521362,
0.23001782596111298... |
Teacher: You are given a concept, and a list of answers. You should generate a question about the concept that leads to the given answer(s).
Teacher: Now, understand the problem? If you are still confused, see the following example:
concept: Cleveland Ohio answers: ['North American Eastern Time Zone']
Solution: what ti... | what is the china money called? | 2 | NIv2 | task1602_webquestion_question_genreation | fs_opt | [
-0.32950958609580994,
0.34899473190307617,
-0.48220616579055786,
-0.29340410232543945,
-0.38917654752731323,
-0.7024343609809875,
-0.2866402268409729,
0.47238689661026,
-0.09268912672996521,
-0.02598375268280506,
0.26627275347709656,
-0.458517849445343,
-0.2222960889339447,
-0.103987768292... |
Given the task definition and input, reply with output. 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). Person... | No | 5 | NIv2 | task1211_atomic_classification_hassubevent | zs_opt | [
0.282845675945282,
0.17835578322410583,
0.3402066230773926,
0.20552575588226318,
-0.46070024371147156,
-0.48866724967956543,
1.1696046590805054,
0.6359533667564392,
-0.5480231642723083,
-0.13385432958602905,
-0.5007495880126953,
-0.23626984655857086,
-0.7308053374290466,
0.3576810359954834... |
Given the task definition and input, reply with output. In this task, you are given a question in English, and your task is to translate it into Persian.
What is the best book for learning Java?
| بهترین کتاب برای یادگیری جاوا چیست؟ | 5 | NIv2 | task652_parsinlu_en_fa_translation | zs_opt | [
-0.6457467675209045,
1.0363051891326904,
-0.09334810078144073,
0.01596992462873459,
0.07578539103269577,
0.3455740213394165,
0.7035083770751953,
-0.013390735723078251,
0.4997020363807678,
0.027358442544937134,
-0.27239128947257996,
0.6446639895439148,
-0.6057878136634827,
0.159524276852607... |
Detailed Instructions: In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the ev... | Yes | 4 | NIv2 | task1212_atomic_classification_hasproperty | fs_opt | [
0.12888650596141815,
-0.16748911142349243,
0.42721617221832275,
-0.007344923447817564,
0.011623155325651169,
-1.3939015865325928,
0.47996193170547485,
1.2992892265319824,
-0.9178576469421387,
0.11442503333091736,
-0.7452141046524048,
-0.472771018743515,
-0.3856200575828552,
-0.324466496706... |
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 that are underh... | Yes | 4 | NIv2 | task607_sbic_intentional_offense_binary_classification | zs_opt | [
-1.1540849208831787,
0.12033982574939728,
0.8987435698509216,
0.8791005611419678,
0.19883882999420166,
-0.5603938102722168,
0.042201898992061615,
0.7283357381820679,
0.3969830274581909,
0.3717401623725891,
-0.11381129920482635,
-0.7461081743240356,
-0.5488741993904114,
-0.7570244073867798,... |
Detailed Instructions: In this task, we ask you to parse restaurant descriptions into a structured data table of key-value pairs. Here are the attributes (keys) and their examples values. You should preserve this order when creating the answer:
name: The Eagle,...
eatType: restaurant, coffee shop,...
food: French... | name[Clowns], eatType[coffee shop], food[French], customer rating[1 out of 5], area[riverside], near[Clare Hall] | 8 | NIv2 | task958_e2e_nlg_text_generation_parse | zs_opt | [
-0.6357756853103638,
0.6862750053405762,
0.17801427841186523,
-0.3630754053592682,
0.0905480831861496,
-0.18387867510318756,
0.619620680809021,
0.18741753697395325,
-0.3219843804836273,
-0.0693698525428772,
0.8297485113143921,
-0.7078016996383667,
-0.8352183103561401,
-0.1281690001487732,
... |
instruction:
In this task, you are given a context sentence containing a blank (_). You are expected to fill the blank with one word to make the sentence convey a cultural anti-stereotype. Anti-stereotype is an idea that goes against a common belief about a particular group of people. Your answer must not contain more ... | propserous
| 9 | NIv2 | task278_stereoset_sentence_generation_antistereotype | fs_opt | [
0.06159171089529991,
0.4219142198562622,
-0.17489424347877502,
0.48533135652542114,
0.2761695683002472,
-0.4827382564544678,
0.5769996047019958,
1.344106912612915,
-0.30848801136016846,
-0.296337366104126,
-0.019207116216421127,
-0.39504045248031616,
-0.37173473834991455,
-0.13960379362106... |
You will be given a definition of a task first, then some input of the task.
In this task you will be given a list of integers. For every element in the list, if the element is even you should divide by 4, if the element is odd you should multiply by 4 then add 2. The output should be a list of numbers that is the resu... | [24.5, -4.5, -8.5, 14, -14.0] | 1 | NIv2 | task368_synthetic_even_or_odd_calculation | zs_opt | [
-0.4237631857395172,
0.7242752313613892,
-0.2035510540008545,
-0.15021120011806488,
0.1579740345478058,
0.20527039468288422,
1.317497968673706,
-0.007128491532057524,
-0.094283327460289,
0.2990955710411072,
-0.6297942996025085,
-0.6252187490463257,
-0.4316309690475464,
-0.4444969892501831,... |
A text is given in Gujarati. Translate it from the Gujarati language to the Tamil language. The translation must not omit or add information to the original sentence.
[Q]: તેના માટે પ્રધાનમંત્રી સુરક્ષિત માતૃત્વ અભિયાન અને પ્રધાનમંત્રી માતૃત્વ વંદના યોજના તેમજ રાષ્ટ્રીય પોષણ અભિયાન અંતર્ગત મિશન મોડમાં કામ ચાલી રહ્યું ... | பிரகதி திட்டம் நமது கூட்டாட்சி அமைப்புக்கு ஒரு பெரிய ஆக்கப்பூர்வ சக்தி என்று அவர் கூறினார்.
| 5 | NIv2 | task1063_pib_translation_gujarati_tamil | fs_opt | [
-0.5831036567687988,
0.043993331491947174,
0.16790704429149628,
-0.33925408124923706,
-0.489314466714859,
-0.7050011157989502,
0.44634270668029785,
0.14479607343673706,
-0.8165332078933716,
0.5411169528961182,
-0.4813103675842285,
-0.5582761764526367,
-0.7200697660446167,
0.099015973508358... |
Detailed Instructions: In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Problem:Tweet: tomorrow there's school. both ... | no | 8 | NIv2 | task196_sentiment140_answer_generation | zs_opt | [
-1.0842756032943726,
0.39799243211746216,
0.5008337497711182,
-0.04511665180325508,
-0.18651407957077026,
-0.7384767532348633,
0.0960153341293335,
0.9468811750411987,
0.3759133219718933,
-0.0492057129740715,
-0.25116342306137085,
-0.49175792932510376,
0.15185809135437012,
-0.75319290161132... |
Given a sentence in Arabic, generate a new Arabic sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it bei... | زوجان حميمان يستطيعان أن يشاهدا الخدعة معاً
| 5 | NIv2 | task414_mickey_ar_sentence_perturbation_generation | fs_opt | [
0.5824595093727112,
1.008204698562622,
-0.3777993321418762,
-0.21466082334518433,
-0.07578463852405548,
-1.0414714813232422,
0.7538182735443115,
0.8253693580627441,
0.5816375613212585,
-0.555740237236023,
-1.1093792915344238,
0.7338167428970337,
-0.40210452675819397,
-0.20726236701011658,
... |
TASK DEFINITION: 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 identi... | yes
| 8 | NIv2 | task108_contextualabusedetection_classification | fs_opt | [
0.11290432512760162,
0.23356327414512634,
0.0545012503862381,
-0.09069226682186127,
-0.08244548738002777,
0.09193167835474014,
1.3839199542999268,
0.5069060325622559,
0.20472218096256256,
0.4166978895664215,
-0.5731765627861023,
-0.03546382859349251,
-0.21141928434371948,
-0.52264851331710... |
You will be given a definition of a task first, then some input of the task.
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 hi... | Si vous voulez débattre de politique, alors vous devriez étudier les questions. | 1 | NIv2 | task406_mickey_fr_sentence_perturbation_generation | zs_opt | [
-0.6813910007476807,
0.6063403487205505,
0.1025543063879013,
-0.001638173358514905,
0.09309989213943481,
-0.08297058939933777,
0.2648594081401825,
-0.030477294698357582,
0.26450711488723755,
-0.17172975838184357,
-0.6209867000579834,
-0.3866797089576721,
0.08835411816835403,
0.046654254198... |
This task is about translating a given English language sentence to French.
Input: Consider Input: Egyptian women were not great feminists maybe, not really.
Output: Il n'a que faire de ses frères qui souffrent?
Input: Consider Input: If you're going to end this marriage... ... you'll do it for yourself, not for an... | Output: Vingt fois huit est égal à 160.
| 2 | NIv2 | task1689_qed_amara_translation | fs_opt | [
-0.020421277731657028,
0.7954150438308716,
-0.38495007157325745,
-0.48948830366134644,
0.03968889266252518,
-0.3124620318412781,
0.672748327255249,
0.39197272062301636,
0.178902268409729,
0.1784496307373047,
-0.6654661893844604,
0.3875768780708313,
-0.5272247195243835,
-0.7742035984992981,... |
Definition: 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 ha... | Yes | 2 | NIv2 | task1202_atomic_classification_xneed | zs_opt | [
0.3623691201210022,
0.2767598032951355,
0.2175154983997345,
-0.20101812481880188,
-0.4636058509349823,
-0.7129313945770264,
1.5595409870147705,
-0.10841652750968933,
-0.43015938997268677,
-0.48681962490081787,
-0.1827244758605957,
-0.2293357253074646,
-0.7749671936035156,
0.389225721359252... |
Given the task definition and input, reply with output. 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".
Bulgarian: Motion for a resolution, English:... | no | 5 | NIv2 | task273_europarl_classification | zs_opt | [
-0.527436375617981,
0.5794515609741211,
0.6238566637039185,
0.2950890064239502,
0.011148212477564812,
-0.37128782272338867,
0.5180720090866089,
0.29198360443115234,
0.6909788250923157,
-0.3452771306037903,
-0.35090887546539307,
0.8345133066177368,
-0.7121633887290955,
0.28317975997924805,
... |
Definition: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Spanish.
Input: 積み木をあげる直線のないサボテン型の積み木だから本物だよ」息子はこれで何をすればいいのか分かりません
Output: | Te daré algunos bloques de construcción son bloques de cactus no rectilíneos, algo totalmente legítimo "". Pero él no sabe realmente qué hacer con ellos. | 2 | NIv2 | task1223_ted_translation_ja_es | zs_opt | [
-0.23830890655517578,
0.10111319273710251,
-0.032758988440036774,
-0.8636054992675781,
-0.6909632682800293,
-0.5380820035934448,
0.9486895203590393,
1.1820663213729858,
0.6632126569747925,
-0.6090419292449951,
-0.04816756397485733,
0.6358881592750549,
-0.6513099670410156,
0.052073612809181... |
In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determ... | No | 4 | NIv2 | task1213_atomic_classification_desires | zs_opt | [
-0.04364633187651634,
0.19412192702293396,
0.4782184660434723,
-0.5075769424438477,
-0.6843894720077515,
-0.4714968800544739,
1.380358338356018,
0.14884532988071442,
-0.4519023895263672,
-0.6461608409881592,
-0.30302315950393677,
-0.37723514437675476,
-0.5681264996528625,
0.527761042118072... |
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... | method | 5 | NIv2 | task1163_coda19_section_classification | zs_opt | [
-0.5501834154129028,
0.7860062122344971,
0.02223767526447773,
-0.05266992747783661,
0.009688735008239746,
0.2899570167064667,
0.18842527270317078,
0.6513388156890869,
0.37721484899520874,
-0.21269971132278442,
-1.0788226127624512,
0.23187831044197083,
-0.08082854747772217,
-0.0885141044855... |
Teacher:This task is about classifying the similarity of two sentences. The sentences can be classified as (a) SIMILAR - similar to each other, and (b) DISSIMILAR - not similar to each other. Sentences that have the same RDF relationship in terms of [subject, predicate, object] are similar to each other. The input is a... | SIMILAR | 6 | NIv2 | task1408_dart_similarity_classification | zs_opt | [
-0.8694332838058472,
0.032720234245061874,
0.38912996649742126,
-0.3451899588108063,
0.3342767357826233,
0.08579380810260773,
1.185096025466919,
0.5351137518882751,
0.11876506358385086,
0.09929624944925308,
-0.5046505331993103,
-0.4195025563240051,
-1.07261323928833,
0.3943229019641876,
... |
In this task, you are given a sentence in the english language. Here, your job is to convert english sentence into the bulgarian language.
--------
Question: Flavourings and certain food ingredients with flavouring properties (
Answer: Ароматизантите и определени хранителни съставки с ароматични свойства (
Question:... | Искам да ви уверя, че ние приемаме консултацията много сериозно.
| 7 | NIv2 | task272_europarl_translation | fs_opt | [
-0.042952775955200195,
0.8505851030349731,
0.3177851140499115,
-0.3749788701534271,
-0.408649206161499,
-0.6800163388252258,
1.1003527641296387,
0.558234691619873,
-0.2511650323867798,
-0.5494458079338074,
-0.5294944047927856,
0.7376952171325684,
-0.8674594163894653,
0.22955811023712158,
... |
This task is to translate the Telugu Language Input to English Language Output
పసికందు యొక్క కీర్తి మరియు చాలా ఎక్కువ | babe of fame and much more | 0 | NIv2 | task1617_cc_alligned_translate_tel_eng | zs_opt | [
-0.4387860894203186,
0.6566886305809021,
0.36262500286102295,
0.15738974511623383,
0.3319240212440491,
-0.31077876687049866,
0.19043245911598206,
-0.9095577001571655,
0.3601202666759491,
0.08133995532989502,
-0.4580231308937073,
-0.2614253759384155,
-0.9818986654281616,
0.2606908082962036,... |
Given the task definition and input, reply with output. In this task you will be given a list of numbers and you need to find the mean (average) of that list. The mean of a list can be found by summing every number in the list then dividing the result by the size of that list. The output should be rounded to 3 decimal ... | -25.45 | 5 | NIv2 | task094_conala_calculate_mean | zs_opt | [
-0.7547650337219238,
0.7169513702392578,
-0.8906664848327637,
-1.0211808681488037,
-0.09016033262014389,
0.6813514828681946,
0.3117823600769043,
-0.20829404890537262,
0.00430632196366787,
-0.13220809400081635,
-1.0386343002319336,
0.7117677927017212,
-0.7939016819000244,
0.3401255011558532... |
The input is a sentence. The sentence includes an emotion. The goal of the task is to classify the emotion in the sentence to one of the classes: 'fear', 'joy', 'anger', 'sadness'. The emotion mainly depends on the adverb within the sentence.
Example: Alphonse feels anxious.
Example solution: fear
Example explanation: ... | Solution: anger | 5 | NIv2 | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | fs_opt | [
-0.35964950919151306,
0.4383486807346344,
0.7229441404342651,
-0.5375620126724243,
-0.24312682449817657,
-0.552693784236908,
1.2500807046890259,
0.3438586890697479,
0.0796312615275383,
-0.3192170560359955,
-0.8220566511154175,
-0.3328516483306885,
-0.4521719217300415,
-0.13322025537490845,... |
Detailed Instructions: In this task, a passage will be given and the goal is to generate a question about temporal relations based on that passage. A temporal relation describes the relation between two things with respect to time e.g., something happens/starts/terminates/... immediately/shortly/usually/... before/afte... | What event has already finished? | 8 | NIv2 | task389_torque_generate_temporal_question | zs_opt | [
-0.6738475561141968,
1.240227222442627,
-0.016243241727352142,
0.15776526927947998,
-0.18008211255073547,
0.5323587656021118,
0.4439047574996948,
0.7784674763679504,
0.3968738913536072,
0.40595120191574097,
-0.500200629234314,
-0.31762564182281494,
-0.8573405742645264,
0.35777169466018677,... |
Instructions: Given a sentence in the Japanese and Lao language. Your task is check if the Lao sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Input: Japanese: 古いダムの材料のうちいくつかは新しいダム建設のために利用され、いくつかは展示用に飾られている。
Lao: ວັດຖຸດິບບາງຢ່າງໄດ້ຖືກເກັບກູ້... | Yes | 3 | NIv2 | task1126_alt_ja_lo_answer_generation | zs_opt | [
-0.5151861310005188,
0.19081062078475952,
-0.20310649275779724,
0.4974164366722107,
-0.02216258831322193,
-1.273963212966919,
0.3063168525695801,
1.0048613548278809,
-0.6635222434997559,
-0.3575408458709717,
-0.24095335602760315,
0.3006843328475952,
-0.6472162008285522,
0.7291155457496643,... |
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'.
Ex Input:
Problem: x + ( 1 / x ) = 1.5 find x ^ 2 + ( 1 / x ^ 2 )
Options: a ) 2.25 , b ) 3.25 , c ) 4.25 , d ) 5.25 , e ) 0.25
Ex Output:
e
Ex Input:
Problem: when 1 / 2... | b
| 1 | NIv2 | task1420_mathqa_general | fs_opt | [
0.3558531701564789,
-0.13088873028755188,
-0.6880229711532593,
0.5653085708618164,
-0.21730443835258484,
0.11519153416156769,
1.150170087814331,
1.464949607849121,
-0.5856373906135559,
0.2805079221725464,
-1.0567960739135742,
-0.19170242547988892,
-0.22075146436691284,
-0.1421412229537964,... |
Given the task definition, example input & output, solve the new input case.
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 | task1200_atomic_classification_xeffect | fs_opt | [
0.6873754262924194,
0.02546190284192562,
-0.030469195917248726,
-0.047498125582933426,
-0.22699473798274994,
-1.067020058631897,
1.1530063152313232,
0.6822642087936401,
-0.6752126216888428,
-0.4635455310344696,
-0.3586123585700989,
-0.4947746992111206,
-0.8109784126281738,
-0.0493318848311... |
In this task, you are given inputs i,j, and A, where i and j are integers and A is a list. You need to return the sum of all the numerical elements in the list A between the positions i and j (including positions i and j). Return 0 if no numerical element is present in the list between the given ranges. i and j will be... | 8826
| 6 | NIv2 | task606_sum_of_all_numbers_in_list_between_positions_i_and_j | fs_opt | [
-0.1357772946357727,
-0.13486312329769135,
-0.9258681535720825,
-0.11297465860843658,
-0.09949503093957901,
-0.22024743258953094,
0.40657252073287964,
0.5192686319351196,
-0.6256383657455444,
0.22684189677238464,
-0.68988037109375,
0.35311874747276306,
0.2104993462562561,
0.195105001330375... |
Detailed Instructions: In this task, 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.
Problem:The machine was working well until it literally fell apart while it was eat to 300 degrees and while I was using it. ... | negative | 8 | NIv2 | task1312_amazonreview_polarity_classification | zs_opt | [
-0.6227161884307861,
-0.4637550711631775,
-0.21467605233192444,
0.22487978637218475,
0.1523151397705078,
-0.3485954999923706,
0.9104207754135132,
0.28124159574508667,
-0.35007089376449585,
0.6530742049217224,
0.06761285662651062,
-0.23525479435920715,
-0.43115586042404175,
-0.3771261572837... |
Definition: Combine the given two facts to write a concluding fact. Note that there should be some parts of the first and second facts that are not mentioned in this conclusion fact. Your combined fact should be the result of a chain between the two facts. Chains form when two facts connect together to produce a conclu... | abalone have a circulatory system with one or two hearts that pump blood. | 2 | NIv2 | task038_qasc_combined_fact | zs_opt | [
0.1529233157634735,
0.28485429286956787,
-0.3403199315071106,
0.19791588187217712,
-0.4137294292449951,
-0.7122607231140137,
-0.18051458895206451,
0.015710007399320602,
-0.36968672275543213,
-0.4664369821548462,
-0.75788414478302,
0.42468008399009705,
-0.7387111783027649,
0.481902539730072... |
Teacher:This is a paraphrasing task. In this task, you're given a sentence and your task is to generate another sentence which express same meaning as the input using different words.
Teacher: Now, understand the problem? Solve this instance: i 'm the one in a hurry , i 'm a `` working girl '' , me ...
Student: | i 'm in a hurry , sweetheart , i 'm a `` working girl '' not rich like you . | 6 | NIv2 | task177_para-nmt_paraphrasing | zs_opt | [
-0.1810312569141388,
0.9842880368232727,
-0.16533954441547394,
-0.49269604682922363,
-0.17129835486412048,
-0.010729502886533737,
-0.6881265640258789,
1.2631425857543945,
0.13605231046676636,
-0.36217689514160156,
-0.43190935254096985,
-0.5148379802703857,
0.12616568803787231,
-0.383542925... |
Two analogies that signify affordances are given in the form "A : B. C : ?". Affordance is the possibility of an action being done on an object, for example book is an affordance of writing. The phrase "A : B" implies that B is an affordance of A. Your task is to replace the question mark (?) with the appropriate affor... | Output: word
| 2 | NIv2 | task1153_bard_analogical_reasoning_affordance | fs_opt | [
0.46897727251052856,
1.028515338897705,
-0.32399752736091614,
0.571568489074707,
-0.07197783887386322,
-0.36073023080825806,
0.8640864491462708,
0.8535534143447876,
0.11156293749809265,
-0.23052439093589783,
-0.3529932498931885,
0.23345956206321716,
-0.3413512706756592,
-0.4328603744506836... |
In this task you will be given an arithmetic operation and you have to find its answer. The operators '+' and '-' have been replaced with new symbols. Specifically, '+' has been replaced with the symbol '@' and '-' with the symbol '#'. You need to perform the operations in the given equation return the answer
[EX Q]: ... | 27768
| 6 | NIv2 | task087_new_operator_addsub_arithmetic | fs_opt | [
-0.4651021361351013,
0.36857372522354126,
-1.2088544368743896,
0.03423745185136795,
-0.6909892559051514,
-0.21184000372886658,
0.23058246076107025,
1.1324821710586548,
0.39271485805511475,
0.12008969485759735,
-0.49055424332618713,
-0.37704795598983765,
0.0008387932321056724,
0.10199622064... |
Given the task definition, example input & output, solve the new input case.
In this task you will be given a list of integers. You should round each integer to the nearest tens place. That means you should round the number to the nearest multiple of 10.
Example: [-83, 53, -48, 8]
Output: [-80, 50, -50, 10]
The output ... | [-610, 350, 260, 180, 630, -340, -930, -550, -720, -910, -380, -180, 180, 80, -990] | 1 | NIv2 | task373_synthetic_round_tens_place | fs_opt | [
-0.5107181668281555,
0.4213749170303345,
-0.4660847783088684,
0.07414659112691879,
0.11745066940784454,
-0.23436839878559113,
0.4733849763870239,
0.5696055889129639,
-0.11839649081230164,
0.22349104285240173,
-0.31440210342407227,
-0.2672802805900574,
-0.2771235704421997,
0.130918323993682... |
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