source stringlengths 17 501k | target stringlengths 0 8.23k | task_name stringlengths 8 85 | task_source stringclasses 4
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Teacher:A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: நாளை அவர் ஆந்திரப்பிரதேசம், தமிழ்நாடு மற்றும் கர்நாடகாவிற்குப் பயணம் மேற்கொள்ள உள்ளார்.
Stud... | वे कल आंध्र प्रदेश, तमिलनाडु और कर्नाटक की यात्रा पर जाएंगे। | task994_pib_translation_tamil_hindi | NIv2 | zs_opt | 6 | train |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
Q: சிறு விவசாயிகள் தங்கள் உற்பத்திப் பொருட்களை நியாயமான விலைக்கு விற்பனை செய்வது, பெரு முதலீட்டாளர்கள் குளிர்பதனக் கிடங்குகள் மற்றும் இதர கட்டமைப்புகளை உருவாக... | भारत सरकार, राष्ट्रीय माध्यमिक शिक्षा अभियान की केन्द्र द्वारा प्रायोजित पूर्व योजना के तहत लड़कियों के लिए आत्मरक्षा प्रशिक्षण को प्रोत्साहन देती रही है।
****
| task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 4 | train |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
Example: முன் கூட்டி அறிந்துகொள்ள முடியாத பருவநிலையினால் ஏற்படும் பாதிப்புகளில் இருந்து விவசாயிகலை பாதுகாக்க பிரதமர் பயிர் காப்பீட்டுத் திட்டம் செயல்படுத்தப்பட... | Solution: हमारे लिए संकल्प की घड़ी है। | task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 5 | train |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
One example is below.
Q: முன் கூட்டி அறிந்துகொள்ள முடியாத பருவநிலையினால் ஏற்படும் பாதிப்புகளில் இருந்து விவசாயிகலை பாதுகாக்க பிரதமர் பயிர் காப்பீட்டுத் திட்டம்... | भविष्य की तकनीक के साथ भारत के इसी कदमताल से ताल मिलाते हुए बीएचयू में अटल incubation centre की शुरूआत की गई है। | task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 9 | train |
Detailed Instructions: A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
Q: இந்த நோக்கத்துக்காக, இந்தியாவில் தொழில் தொடங்குவோம் என்ற பிரச்சாரத்தை நாங்கள் தொடங்கியுள்ளோம்.
A: | इस उद्देश्य के लिए, हमने स्टार्ट-अप इंडिया अभियान शुरू किया है। | task994_pib_translation_tamil_hindi | NIv2 | zs_opt | 9 | train |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
[EX Q]: இந்தியாவைத் தவிர வேறு 33 நாடுகளைச் சேர்ந்த 329 மாணவர்கள் இன்று பட்டம் பெறுகிறார்கள்.
[EX A]: विश्वविद्यालय से स्नातक बनकर निकलने वाले छात्रों में से 3... | आज का सहकार आंदोलन जो देश के अनेक गांवों की अर्थव्यवस्था का मजबूत आधार बन चुका है यह सरदार साहब की ही दीर्घ दृष्टि का परिणाम है।
| task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 6 | train |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
Q: கூடுதலான முறைப்படுத்தலால் கூடுதல் வருவாய், ஏழைகளுக்குக் கூடுதல் நிதி, சிறந்த அடிப்படைக் கட்டமைப்பு, நமது மக்களின் சிறப்பான வாழ்க்கைத்தரம் சாத்தியமாகி உள்ளத... | इसरो के ध्रुवीय सैटेलाइट लांच वाहन ने अपनी 42वीं उड़ान पीएसएलवी-सी40 से 12 जनवरी, 2018 को सतीश धवन अंतरिक्ष केन्द्र एसएचएआर, श्रीहरिकोटा से 30 सह-यात्री सैटेलाइटों के साथ 710 किलोग्राम का कार्टोसेट-2 श्रृंखला का दूरसंवेदी सैटेलाइट लांच किया।
****
| task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 4 | train |
instruction:
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
question:
இது இயற்கையின் மீதான அவர்களின் மரியாதை மற்றும் நல்லிணக்கத்துக்கு சான்றாக அமைகிறது.
answer:
इससे प्रकृति के प्रति उनके सम्मान और सामंजस्य... | प्रधानमंत्री श्री नरेन्द्र मोदी की अध्यक्षता में केन्द्रीय मंत्रिमंडल (कैबिनेट) नेनवीन एवं नवीकरणीय ऊर्जा के क्षेत्र में तकनीकी द्विपक्षीय सहयोग पर भारत और फ्रांस के बीच सहमति पत्र (एमओयू) को मंजूरी दे दी है।
| task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 9 | train |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
--------
Question: மேலும், உங்களுடைய திட்டங்களை முடிவு செய்யும்போது, இந்த விஷயங்களையும் மனதில் கொள்வீர்கள் என்று நான் நம்புகிறேன்.
Answer: मुझे उम्मीद है कि अ... | ये बात सही है जब चम्पारण सत्याग्रह महात्मा गांधी ने किया होगा, जब आजादी के लिए बिगुल बजाया होगा तो कोई दूसरे ही दिन सुबह आजादी मिल जाने वाली है, ऐसा थोड़ा होगा।
| task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 7 | test |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
Input: Consider Input: உள்ளூர் விவசாயிகளை தொழில்நுட்பத்துடன் தொடர்புபடுத்துவதற்கு நீங்கள் தொடர்ச்சியாக முயற்சிகள் எடுக்க வேண்டும்.
Output: स्थानीय किसानों को... | Output: कावारत्ती में भारतीय नौसेना के हेलीकॉप्टर आईएनएस द्वीप रक्षक द्वारा बितरा द्वीप के लिए सूखी रसद और खाने के लिए तैयार भोजन की आपदा राहत सामग्री को भेजा गया।
| task994_pib_translation_tamil_hindi | NIv2 | fs_opt | 2 | validation |
In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Let me give you an example: Hello! I would love to learn about Antigua and Barbuda today.
Antigua and Barbuda is an island nation in the Caribbean Sea. The country is part of the British Commonwealth.
T... | Bosnia and Herzegovina | task578_curiosity_dialogs_answer_generation | NIv2 | fs_opt | 8 | train |
Given the task definition and input, reply with output. In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Hello
Hi, what can I help you with today?
I'd like to learn about Arizona, please.
Ok. Well Arizona is located in the Southwest United States, a... | Arizona | task578_curiosity_dialogs_answer_generation | NIv2 | zs_opt | 5 | train |
Detailed Instructions: In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Problem:what can you tell me about democratic republic of the congo?
Hello. The official language of the Democratic Republic of the Congo is French.
what can you tell me about its ... | Democratic Republic of the Congo | task578_curiosity_dialogs_answer_generation | NIv2 | zs_opt | 8 | train |
Part 1. Definition
In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Part 2. Example
Hello! I would love to learn about Antigua and Barbuda today.
Antigua and Barbuda is an island nation in the Caribbean Sea. The country is part of the British Commonwealt... | Kolkata | task578_curiosity_dialogs_answer_generation | NIv2 | fs_opt | 7 | train |
In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
--------
Question: Hello. I would like to learn about Saint Lucia.
St Lucia is considered part of the British Windward Islands colony
Can you tell me about their culture?
St lucia's has hosted a jazz f... | Chile
| task578_curiosity_dialogs_answer_generation | NIv2 | fs_opt | 7 | train |
Detailed Instructions: In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Problem:What can you tell me about Japan?
Here is something, Japan has close ties to the United States.
Tell me more.
Okay, would you like to know about Japan's agriculture?
I'... | Japan | task578_curiosity_dialogs_answer_generation | NIv2 | zs_opt | 8 | train |
In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Example: Hello! I would love to learn about Antigua and Barbuda today.
Antigua and Barbuda is an island nation in the Caribbean Sea. The country is part of the British Commonwealth.
That is very interest... | Solution: Missouri | task578_curiosity_dialogs_answer_generation | NIv2 | fs_opt | 5 | train |
Definition: In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Input: Hello, can you please tell me about Finland?
Hello, Finland is in Northern Europe. It's official languages are Finnish and Swedish.
thank you! can you tell me more about their geograph... | Finland | task578_curiosity_dialogs_answer_generation | NIv2 | zs_opt | 2 | train |
Definition: In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
Input: Hello, can you please tell me a little bit about Palau?
Sure! The name Palau entered the English language from the Spanish Los Palaos , via the German Palau. Palau is a member of the Nau... | Palau | task578_curiosity_dialogs_answer_generation | NIv2 | zs_opt | 2 | test |
In this task, you are given dialogue, and you have to find the most critical location in the given conversation.
One example: Hello! I would love to learn about Antigua and Barbuda today.
Antigua and Barbuda is an island nation in the Caribbean Sea. The country is part of the British Commonwealth.
That is very inte... | Somalia | task578_curiosity_dialogs_answer_generation | NIv2 | fs_opt | 6 | validation |
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
One example is below.
Q: 全て肋骨の間から行うのです
A: Wszystko jest robione pomiędzy żebrami.
Rationale: The Japanese sentence is correctly translated into Polish, because the meaning is preserved.
Q: はるか昔に書かれたユダヤ教の聖典にはこのことが書かれています「我々... | Już Talmud dowodził, że postrzegamy rzeczy nie według nich, ale według samych siebie. | task1097_ted_translation_ja_pl | NIv2 | fs_opt | 9 | train |
instruction:
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
question:
一番上の線は実験中の普通のネズミの体温です点線は実験中の室温を示します
answer:
Na samej górze widzimy zapis normalnej temperatury ciała myszy, spójrzmy na linię przerywaną.
question:
（ 笑 ） BF ： ジャグリングがひどい評価を受けた
answer:
(Śmiech) Żong... | Bo to, właściwie nie powiedziałem wcześniej, to jest pozaszkieletowy implant...
| task1097_ted_translation_ja_pl | NIv2 | fs_opt | 9 | train |
Definition: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
Input: そこで今日は俺自身と外から持ってきたこの壁について話をしたい
Output: | Opowiem o sobie i tej ścianie, którą próbuję udomowić. | task1097_ted_translation_ja_pl | NIv2 | zs_opt | 2 | train |
Q: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
しかし先ほど申し上げたように魚についてなら一番分かっているということです
A: | Ryby jednak są najbardziej znane. | task1097_ted_translation_ja_pl | NIv2 | zs_opt | 7 | train |
Q: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
北端が北回帰線で南端が南回帰線だぐらいしか南端が南回帰線だぐらいしか知らなかった私が驚いたのは回帰線が緯度やー国境といった製図上の線でなくて地球の傾きで決まっていてさらには年々変化して
A: | Na północy jest Zwrotnik Raka a na południu Koziorożca, tyle wiedziałem. Ale zdziwił mnie ten fakt: To nie są linie kartograficzne jak równoleżniki czy granice państw, to zmienne zjawiska astronomiczne spowodowane nachyleniem Ziemi. | task1097_ted_translation_ja_pl | NIv2 | zs_opt | 7 | train |
Q: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
では私たちに何が必要なのでしょう
A: | Czego więc potrzeba? | task1097_ted_translation_ja_pl | NIv2 | zs_opt | 7 | train |
Definition: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
Input: 多くの人が洞窟潜水は恐らく最も危険な活動の一つだといいます
Output: | Wielu ludzi twierdzi, że nurkowanie w jaskiniach jest bardzo niebezpieczne. | task1097_ted_translation_ja_pl | NIv2 | zs_opt | 2 | train |
TASK DEFINITION: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
PROBLEM: 去年は月に一度「確信のなさの法則」と題したコラムを書きましたハイゼンベルグって誰か知りませんけど今となってはその言葉はわかります不確定性原理ですよね
SOLUTION: Tak więc od roku co miesiąc pisałam artykuły w kolumnie zatytułowanej "" Zasady nieoznaczoności "". Nie wiem, ... | W zasadzie, ludzie byli poprostu zbyt entuzjastyczni na początku XXI wieku, myśląc, że Ameryka może wszystko, co doprowadziło nas do kilku katastrofalnych przygód w polityce zagranicznej i teraz znów znajdujemy się w odwrocie.
| task1097_ted_translation_ja_pl | NIv2 | fs_opt | 8 | train |
Part 1. Definition
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
Part 2. Example
全て肋骨の間から行うのです
Answer: Wszystko jest robione pomiędzy żebrami.
Explanation: The Japanese sentence is correctly translated into Polish, because the meaning is preserved.
Part 3. Exercise
これ... | Spójrzcie tutaj. Tak było w 1975. | task1097_ted_translation_ja_pl | NIv2 | fs_opt | 7 | test |
Instructions: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
Input: 親友のデイビッドが考え込んでいる私のところにやって来て言いました “お前のことは18歳の時から知っている
Output: | Mój bliski przyjaciel David zobaczył co sobie myślałem. Przyszedł do mnie i powiedział, "" Lewis, znam cię od kiedy miałem 18 lat. | task1097_ted_translation_ja_pl | NIv2 | zs_opt | 3 | validation |
In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
Q: Sam loved his ne... | Not Answerable
****
| task290_tellmewhy_question_answerability | NIv2 | fs_opt | 4 | train |
In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
[Q]: Jim has scienc... | Answerable
| task290_tellmewhy_question_answerability | NIv2 | fs_opt | 5 | train |
In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
Ex Input:
Rosie com... | Answerable
| task290_tellmewhy_question_answerability | NIv2 | fs_opt | 1 | train |
In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
Ex Input:
Jimmy lov... | Not Answerable
| task290_tellmewhy_question_answerability | NIv2 | fs_opt | 1 | train |
In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
Example Input: Jill... | Not Answerable
| task290_tellmewhy_question_answerability | NIv2 | fs_opt | 3 | train |
In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
Q: I visited a deale... | Answerable | task290_tellmewhy_question_answerability | NIv2 | zs_opt | 4 | train |
Definition: In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
Input: G... | Answerable | task290_tellmewhy_question_answerability | NIv2 | zs_opt | 2 | train |
Detailed Instructions: In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line characte... | Answerable | task290_tellmewhy_question_answerability | NIv2 | zs_opt | 9 | train |
In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line character.
Q: Jenny has never l... | Not Answerable | task290_tellmewhy_question_answerability | NIv2 | zs_opt | 4 | test |
Detailed Instructions: In this task you are given a story and a question regarding that story. You must judge whether the question is answerable based on the info given to you. Label the instances as "Answerable" or "Not Answerable" based on your judgment. the story and the question are separated by a new line characte... | Answerable | task290_tellmewhy_question_answerability | NIv2 | zs_opt | 9 | validation |
Detailed Instructions: You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answe... | A complex machine by its nature is composed of multiple simple machines. | task045_miscellaneous_sentence_paraphrasing | NIv2 | zs_opt | 9 | train |
Part 1. Definition
You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to... | All chemical reactions must include a reactant and a product. | task045_miscellaneous_sentence_paraphrasing | NIv2 | fs_opt | 7 | train |
You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to the question from ... | All chemical reactions must include a reactant and a product.
| task045_miscellaneous_sentence_paraphrasing | NIv2 | fs_opt | 7 | train |
You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to the question from ... | Neptune can be located in eighth place away from our sun.
| task045_miscellaneous_sentence_paraphrasing | NIv2 | fs_opt | 1 | train |
Detailed Instructions: You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answe... | Categories of the periodic table of elements include categories like metals and nonmetals. | task045_miscellaneous_sentence_paraphrasing | NIv2 | fs_opt | 4 | train |
You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to the question from ... | In the human body, the esophagus, the stomach, and the intestines are the structures that make up the digestive system.
| task045_miscellaneous_sentence_paraphrasing | NIv2 | fs_opt | 1 | train |
You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to the question from ... | Four phases make up mitosis. | task045_miscellaneous_sentence_paraphrasing | NIv2 | zs_opt | 4 | train |
Detailed Instructions: You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answe... | In our solar system the sun is that the center. | task045_miscellaneous_sentence_paraphrasing | NIv2 | zs_opt | 9 | train |
You will be given a definition of a task first, then some input of the task.
You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still su... | At low temperatures gases and liquids become solids. | task045_miscellaneous_sentence_paraphrasing | NIv2 | zs_opt | 1 | test |
You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to the question from ... | Actin filaments, which are components of the cytoskeleton, are the muscle type of cell function relied on by microfilaments. | task045_miscellaneous_sentence_paraphrasing | NIv2 | zs_opt | 0 | validation |
Detailed Instructions: This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The... | [['Gangsters 2', 'PUBLISHER(S)', 'Eidos Interactive']] | task1410_dart_relationship_extraction | NIv2 | fs_opt | 4 | train |
Definition: This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The input is a... | [['The Eagle', 'eatType', 'restaurant'], ['The Eagle', 'priceRange', 'moderate'], ['The Eagle', 'customer rating', '1 out of 5'], ['The Eagle', 'area', 'riverside']] | task1410_dart_relationship_extraction | NIv2 | zs_opt | 2 | train |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must b... | [['The Eagle', 'eatType', 'coffee shop'], ['The Eagle', 'food', 'French'], ['The Eagle', 'priceRange', 'more than £30'], ['The Eagle', 'customer rating', 'low'], ['The Eagle', 'area', 'riverside'], ['The Eagle', 'familyFriendly', 'yes'], ['The Eagle', 'near', 'Burger King']] | task1410_dart_relationship_extraction | NIv2 | fs_opt | 0 | train |
Detailed Instructions: This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The... | [['Blue Spice', 'eatType', 'restaurant'], ['Blue Spice', 'priceRange', 'high']] | task1410_dart_relationship_extraction | NIv2 | zs_opt | 9 | train |
Given the task definition and input, reply with output. This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and sem... | [['[TABLECONTEXT]', 'NAME', 'Wilhelm Keppler'], ['Wilhelm Keppler', 'SENTENCE', "10 years' imprisonment; released 1951"], ['Wilhelm Keppler', 'FUNCTION', "Secretary of State; Hitler's advisor for economy"], ['[TABLECONTEXT]', '[TITLE]', 'Ministries Trial']] | task1410_dart_relationship_extraction | NIv2 | zs_opt | 5 | train |
Part 1. Definition
This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The inp... | [['1992', 'AVG._FINISH', '29.0'], ['[TABLECONTEXT]', '[TITLE]', 'Chad Little NASCAR Nationwide Series'], ['1992', 'WINNINGS', '$1,400'], ['[TABLECONTEXT]', 'YEAR', '1992']] | task1410_dart_relationship_extraction | NIv2 | fs_opt | 7 | train |
Q: This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The input is a sentence... | [['Cotto', 'eatType', 'restaurant'], ['Cotto', 'food', 'Japanese'], ['Cotto', 'priceRange', 'cheap'], ['Cotto', 'near', 'The Portland Arms']] | task1410_dart_relationship_extraction | NIv2 | zs_opt | 7 | train |
Detailed Instructions: This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The... | [['Wildwood', 'eatType', 'pub'], ['Wildwood', 'food', 'Indian'], ['Wildwood', 'priceRange', 'moderate'], ['Wildwood', 'customer rating', 'high']] | task1410_dart_relationship_extraction | NIv2 | zs_opt | 8 | train |
Teacher: This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The input is a se... | [['Manhattan', 'LEADER_NAME', 'Cyrus Vance, Jr.']] | task1410_dart_relationship_extraction | NIv2 | fs_opt | 2 | test |
You will be given a definition of a task first, then some input of the task.
This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture ... | [['Kaç Para Kaç', 'FILM_TITLE_USED_IN_NOMINATION', 'Run for Money']] | task1410_dart_relationship_extraction | NIv2 | zs_opt | 1 | validation |
Detailed Instructions: Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversatio... | No | task1442_doqa_movies_isanswerable | NIv2 | zs_opt | 8 | train |
Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversation question has a prefix... | Yes | task1442_doqa_movies_isanswerable | NIv2 | fs_opt | 8 | train |
Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversation question has a prefix... | Yes | task1442_doqa_movies_isanswerable | NIv2 | fs_opt | 8 | train |
Detailed Instructions: Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversatio... | Yes | task1442_doqa_movies_isanswerable | NIv2 | fs_opt | 4 | train |
You will be given a definition of a task first, then some input of the task.
Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The... | Yes | task1442_doqa_movies_isanswerable | NIv2 | zs_opt | 1 | train |
Given the task definition and input, reply with output. Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the pr... | Yes | task1442_doqa_movies_isanswerable | NIv2 | zs_opt | 5 | train |
Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversation question has a prefix... | Yes
****
| task1442_doqa_movies_isanswerable | NIv2 | fs_opt | 4 | train |
Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversation question has a prefix... | Yes | task1442_doqa_movies_isanswerable | NIv2 | fs_opt | 8 | train |
Given the task definition and input, reply with output. Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the pr... | No | task1442_doqa_movies_isanswerable | NIv2 | zs_opt | 5 | test |
Definition: Given a paragraph about movies and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversation question ... | No | task1442_doqa_movies_isanswerable | NIv2 | zs_opt | 2 | validation |
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: Great Chips - No after taste... Seem to be much better for me. Need to buy the big bags now.
Summary: Great Chips - Love the Salt & Vinegar
A... | True | task590_amazonfood_summary_correction_classification | NIv2 | zs_opt | 4 | train |
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]: I hate to admit I miss the lard. I was the one in your 4th-grade class who unscrewed the Oreo, ate all the white middle, licked the wafers c... | True
| task590_amazonfood_summary_correction_classification | NIv2 | fs_opt | 5 | train |
Given the task definition, example input & output, solve the new input case.
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".
Example: I have bought several of the Vitality canned dog food produc... | False | task590_amazonfood_summary_correction_classification | NIv2 | fs_opt | 1 | train |
Detailed Instructions: 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: Got these free in the Newman's Own Dog Food bag. My dogs have been fans of the other Newman's treats in the past, but th... | False | task590_amazonfood_summary_correction_classification | NIv2 | zs_opt | 9 | train |
Q: 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".
I found it much tastier than the plain tuna pouches out there. Excellent quality, and no need to 'dress it up'. I put it the micro on about 20... | True | task590_amazonfood_summary_correction_classification | NIv2 | zs_opt | 7 | train |
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: The first time I tried this product to make pancakes, I thought it was terrible. I made it according to the directions and used the "right" m... | False
****
| task590_amazonfood_summary_correction_classification | NIv2 | fs_opt | 4 | train |
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".
Sea salt is more easily administered with a salt mill. This is just a salt shaker that delivers uncontrollable amounts of sea salt and anti-cakin... | True | task590_amazonfood_summary_correction_classification | NIv2 | zs_opt | 0 | train |
Detailed Instructions: 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".
See one example below:
Problem: I have bought several of the Vitality canned dog food products and have found them all to b... | False | task590_amazonfood_summary_correction_classification | NIv2 | fs_opt | 4 | train |
TASK DEFINITION: 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".
PROBLEM: I purchased this coffee on sale at my local Vons. They had it on sale for $4.99 a bag so I bought four bags -- can't bea... | False
| task590_amazonfood_summary_correction_classification | NIv2 | fs_opt | 8 | test |
You will be given a definition of a task first, then some input of the task.
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".
I just ordered this, came today and thought I would just try it, wel... | True | task590_amazonfood_summary_correction_classification | NIv2 | zs_opt | 1 | validation |
In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is undermining.
Example Input: claim: More gun control laws should be enacted.... | undermine
| task738_perspectrum_classification | NIv2 | fs_opt | 3 | train |
Detailed Instructions: In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is undermining.
Problem:claim: We should allow military ... | undermine | task738_perspectrum_classification | NIv2 | zs_opt | 8 | train |
In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is undermining.
claim: The niqab and other face coverings in schools must be b... | undermine | task738_perspectrum_classification | NIv2 | zs_opt | 0 | train |
In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is undermining.
Let me give you an example: claim: Music containing lyrics tha... | support | task738_perspectrum_classification | NIv2 | fs_opt | 8 | train |
You will be given a definition of a task first, then some input of the task.
In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is... | undermine | task738_perspectrum_classification | NIv2 | zs_opt | 1 | train |
Definition: In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is undermining.
Input: claim: Christianity is the greatest deceptio... | undermine | task738_perspectrum_classification | NIv2 | zs_opt | 2 | train |
You will be given a definition of a task first, then some input of the task.
In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is... | support | task738_perspectrum_classification | NIv2 | zs_opt | 1 | train |
Given the task definition and input, reply with output. In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is undermining.
claim:... | undermine | task738_perspectrum_classification | NIv2 | zs_opt | 5 | train |
Given the task definition, example input & output, solve the new input case.
In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is... | undermine | task738_perspectrum_classification | NIv2 | fs_opt | 1 | test |
In this task you will be given a claim and a perspective. You should determine whether that perspective supports or undermines the claim. If the perspective could possibly convince someone with different view, it is supporting, otherwise it is undermining.
Example Input: claim: Ghana’s ban on smoking in public places ... | undermine
| task738_perspectrum_classification | NIv2 | fs_opt | 3 | validation |
You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You should not change any ... | PersonX was an asset to their employer but PersonY was not because _ was very traitorous. | task035_winogrande_question_modification_person | NIv2 | fs_opt | 8 | train |
You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You should not change any ... | The essays that PersonX wrote for college applications read better than PersonY's because _ is a more basic writer.
| task035_winogrande_question_modification_person | NIv2 | fs_opt | 1 | train |
Given the task definition, example input & output, solve the new input case.
You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its anton... | PersonX collected barbies when she was younger but not PersonY because _ was a tom boy. | task035_winogrande_question_modification_person | NIv2 | fs_opt | 1 | train |
Teacher: You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You should not ch... | PersonX would make a poor kindergarten teacher, unlike PersonY, because _ was patient with kids. | task035_winogrande_question_modification_person | NIv2 | fs_opt | 2 | train |
Teacher:You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You should not cha... | The ex girlfriend of PersonX just went and slept with his friend, PersonY, so _ feels guilty. | task035_winogrande_question_modification_person | NIv2 | zs_opt | 6 | train |
You will be given a definition of a task first, then some input of the task.
You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its anton... | PersonX broke up with PersonY after they started dating although _ was still in love with them. | task035_winogrande_question_modification_person | NIv2 | zs_opt | 1 | train |
You will be given a definition of a task first, then some input of the task.
You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its anton... | PersonX could remember where they were the night of the first, but PersonY could not, because _ had consulted their journal. | task035_winogrande_question_modification_person | NIv2 | zs_opt | 1 | train |
You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You should not change any ... | PersonX enjoyed watching the horror movie much more than PersonY, because _ disliked feeling scared.
| task035_winogrande_question_modification_person | NIv2 | fs_opt | 6 | train |
You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You should not change any ... | PersonX accidentally burned PersonY with a hot pan. _ felt lots of pain and accepted medical aid.
****
| task035_winogrande_question_modification_person | NIv2 | fs_opt | 4 | test |
TASK DEFINITION: You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You shoul... | The English reading skills of PersonX are far inferior to PersonY because _ is a native English speaker.
| task035_winogrande_question_modification_person | NIv2 | fs_opt | 8 | validation |
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