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Teacher:In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Teacher: Now, understand the problem? Solve this instance: English: What Would a Canadian Cancer Cohort Cost?
French: Que... | no | task831_giga_fren_classification | NIv2 | zs_opt | 6 | train |
In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Ex Input:
English: Which target market(s)?
French: Quel(s) marché(s) cibler?
Ex Output:
yes
Ex Input:
English: What should ou... | no
| task831_giga_fren_classification | NIv2 | fs_opt | 1 | train |
Detailed Instructions: In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Problem:English: What do you see as management priorities as we move forward?
French: Quelles seront vos p... | yes | task831_giga_fren_classification | NIv2 | zs_opt | 8 | train |
Teacher: In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Teacher: Now, understand the problem? If you are still confused, see the following example:
English: What can I do?
Fren... | no | task831_giga_fren_classification | NIv2 | fs_opt | 2 | train |
In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Example Input: English: Why is productive research time wasted by asking numerous reviewers to review these multiple applications?... | yes
| task831_giga_fren_classification | NIv2 | fs_opt | 3 | 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.
In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
English: ... | yes | task831_giga_fren_classification | NIv2 | fs_opt | 0 | train |
Part 1. Definition
In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Part 2. Example
English: What can I do?
French: Que puis je faire?
Answer: yes
Explanation: English sentence i... | no | task831_giga_fren_classification | NIv2 | fs_opt | 7 | train |
Q: In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
English: What has been the influence of other factors on the overall effectiveness of Institutes?
French: • Quel est votre niv... | no | task831_giga_fren_classification | NIv2 | zs_opt | 7 | train |
Given the task definition and input, reply with output. In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
English: What resources do we need to develop Canadian content in health e... | no | task831_giga_fren_classification | NIv2 | zs_opt | 5 | test |
In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Q: English: What documents do I need to provide?
French: Quels documents dois-je produire?
A: | yes | task831_giga_fren_classification | NIv2 | zs_opt | 4 | validation |
The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is translated as hundred thousan... | The time was fixed at one p.m., as an approximation, since it was impossible to determine the precise moment when life left the President.
| task1703_ljspeech_textmodification | NIv2 | fs_opt | 7 | train |
Detailed Instructions: The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is transl... | had duty assignments beginning no later than eight a.m. that morning. | task1703_ljspeech_textmodification | NIv2 | zs_opt | 9 | train |
Given the task definition and input, reply with output. The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the ... | As a political leader, the President wished to resolve the factional controversy within the Democratic Party in Texas before the election of nineteen sixty four. | task1703_ljspeech_textmodification | NIv2 | zs_opt | 5 | train |
The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is translated as hundred thousan... | In March nineteen sixty three, while attempting to locate Marina Oswald, | task1703_ljspeech_textmodification | NIv2 | fs_opt | 3 | train |
Detailed Instructions: The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is transl... | reveals that Hill first placed his hand on the Presidential car at frame three forty three, thirty frames | task1703_ljspeech_textmodification | NIv2 | zs_opt | 9 | train |
The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is translated as hundred thousan... | was also reported in the October one, nineteen sixty three, issue of the Worker, to which Oswald also subscribed. | task1703_ljspeech_textmodification | NIv2 | fs_opt | 3 | train |
Definition: The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is translated as hun... | This was on the last day of eighteen twenty nine. In the following session Sir Robert Peel brought in a bill to consolidate the acts relating to forgery. | task1703_ljspeech_textmodification | NIv2 | zs_opt | 2 | train |
The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is translated as hundred thousan... | On the fourteenth June, eighteen hundred, there were one hundred ninety nine debtors and two hundred eighty nine felons in the prison. | task1703_ljspeech_textmodification | NIv2 | zs_opt | 4 | train |
Definition: The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is translated as hun... | By the thirty one George the third c. forty six, s. five, | task1703_ljspeech_textmodification | NIv2 | zs_opt | 2 | test |
Teacher:The task is reading a paragraph containing numbers as digits. The digits can be used to represent Quantity, Dates and Time, Addresses or Positions. Convert the digits into their text equivalents. If a number has a prefix, postfix or punctuation preserve it in the text equivalent. 100000 is translated as hundred... | When Governor Connally called at the White House on October four to discuss the details of the visit, | task1703_ljspeech_textmodification | NIv2 | zs_opt | 6 | validation |
In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing a sentence that gives n... | Because it is a part of the house.
| task135_winowhy_wrong_reason_generation | NIv2 | fs_opt | 3 | train |
Given the task definition, example input & output, solve the new input case.
In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and t... | Because they were the last cookie to come out, and because the other cookies had more sugar and butter. | task135_winowhy_wrong_reason_generation | NIv2 | fs_opt | 1 | train |
Q: In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing a sentence that give... | Because his father is Bill's grandfather (who has not yet been named), as well as Bill's mom. | task135_winowhy_wrong_reason_generation | NIv2 | zs_opt | 7 | train |
Instructions: In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing a sentenc... | Because GOODMAN TO REFER XENOPHANES. | task135_winowhy_wrong_reason_generation | NIv2 | zs_opt | 3 | 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.
In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify... | Because he was in the habit of taking the name of a friend when he died, to which he had. | task135_winowhy_wrong_reason_generation | NIv2 | fs_opt | 0 | train |
In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing a sentence that gives n... | Because they were also interested in the new movie.I'll get back to the 'They' later. | task135_winowhy_wrong_reason_generation | NIv2 | fs_opt | 6 | train |
In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing a sentence that gives n... | Because yes agree that it refers to the house. | task135_winowhy_wrong_reason_generation | NIv2 | zs_opt | 0 | train |
Detailed Instructions: In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing ... | Because MORE LIKELY TO REFER THE CAT. | task135_winowhy_wrong_reason_generation | NIv2 | fs_opt | 4 | train |
In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing a sentence that gives n... | Because the gang was not only dealing drugs but also trying to run the drug trade.
| task135_winowhy_wrong_reason_generation | NIv2 | fs_opt | 3 | test |
Teacher:In this task you need to give wrong reasons to justify the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and and a question about how to justify the coreference between a noun phrase and the target pronoun. Good practices involve (1) writing a sentence that... | Because of the lake, but it could also be a reference to the lake's shape and the fact that. | task135_winowhy_wrong_reason_generation | NIv2 | zs_opt | 6 | validation |
Teacher: Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial tra... | काला फ्रेम छवि चुनें | task877_kde4_translation | NIv2 | fs_opt | 2 | train |
Detailed Instructions: Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But on... | 1: इटरेशन्स यूनिट बेलआउट | task877_kde4_translation | NIv2 | zs_opt | 9 | train |
Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial translation ... | यह लिंक शब्दसंग्रह सन्दर्भों के लिए है. | task877_kde4_translation | NIv2 | zs_opt | 0 | train |
You will be given a definition of a task first, then some input of the task.
Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both ... | पढ़ें फ़ाइल जानकारी% 1 चयनित | task877_kde4_translation | NIv2 | zs_opt | 1 | train |
Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial translation ... | सहेजने के लिए गिम्प स्तर फ़ाइल
| task877_kde4_translation | NIv2 | fs_opt | 0 | train |
Instructions: Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partia... | डाटाबेस स्कीमा असंगत है. | task877_kde4_translation | NIv2 | zs_opt | 3 | train |
Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial translation ... | यहां पर निचले दाएं क्षेत्र का रंग सेट करें. | task877_kde4_translation | NIv2 | zs_opt | 4 | train |
Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial translation ... | लघुछविपट्टी वस्तु औज़ार- युक्ति दिखाएँ
| task877_kde4_translation | NIv2 | fs_opt | 1 | train |
Given the task definition, example input & output, solve the new input case.
Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both ... | गुम तिथियों सहित छवियाँ व वीडियो ढूंढें | task877_kde4_translation | NIv2 | fs_opt | 1 | test |
Your task is to localize given English phrase into Hindi language. When localising, follow these rules - (1) General names and concepts can be translated (2) Domain specific names can just be transliterated (3) Localised phrases can have both partial translated and transliterated parts (4) But only partial translation ... | इस बटन के जरिए, वक्र क़िस्म को खिंचाव के जरिए समतल बना सकते हैं. | task877_kde4_translation | NIv2 | zs_opt | 4 | validation |
You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phrase and is ... | Yes | task457_matres_conditional_classification | NIv2 | fs_opt | 3 | train |
You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phrase and is ... | No
| task457_matres_conditional_classification | NIv2 | fs_opt | 7 | train |
You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phrase and is ... | Solution: Yes | task457_matres_conditional_classification | NIv2 | fs_opt | 5 | train |
You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phrase and is ... | Yes | task457_matres_conditional_classification | NIv2 | fs_opt | 6 | train |
Given the task definition and input, reply with output. You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is c... | Yes | task457_matres_conditional_classification | NIv2 | zs_opt | 5 | train |
You will be given a definition of a task first, then some input of the task.
You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea o... | Yes | task457_matres_conditional_classification | NIv2 | zs_opt | 1 | train |
You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phrase and is ... | Yes | task457_matres_conditional_classification | NIv2 | zs_opt | 0 | train |
Teacher: You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phras... | No | task457_matres_conditional_classification | NIv2 | fs_opt | 2 | train |
You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phrase and is ... | No | task457_matres_conditional_classification | NIv2 | zs_opt | 4 | test |
Teacher:You will be given a context and a verb separated with a newline character. You have to decide if the given verb implies a hypothetical or conditioned action or not. We say a verb is hypothetical if it involves or is based on a suggested idea or theory. A verb is conditional if it appears in a conditional phrase... | No | task457_matres_conditional_classification | NIv2 | zs_opt | 6 | validation |
TASK DEFINITION: In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal ... | Ikọ̀ agbábọ́ọ̀lù Russia s̩apá wọn láti dámì-ayò ọ̀hún padà, ṣùgbọ́n omi pọ̀ ju ọkà lọ.
| task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 8 | train |
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form. The output ... | However, several homes of Witnesses were flooded.
| task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 1 | train |
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form. The output ... | Àwọn Ilé Ẹjọ́ Gíga ní Uzbekistan Dájọ́ Pé Àwọn Ẹlẹ́rìí Jèhófà Lẹ́tọ̀ọ́ Láti Ní Àwọn Ìwé Tó Dá Lórí Bíbélì | task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 3 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: ... | Ìròyìn tá a kọ́kọ́ gbọ́ jẹ́ ká mọ̀ pé àwọn akéde ọgọ́rùn-ún mẹ́rin, àti àádọ́rin lé mẹ́rin [484] ti sá kúrò nílé, wọ́n sì lọ ń gbé pẹ̀lú àwọn arákùnrin míì tàbí pẹ̀lú àwọn mọ̀lẹ́bí wọn tó ń gbé ní apá ibi tí àlááfíà wà. | task1619_menyo20k_mt_en_yo_translation | NIv2 | zs_opt | 1 | train |
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form. The output ... | Rọ́ṣíà Dájú Sọ Àwọn Àgbàlàgbà Ẹlẹ́rìí Jèhófà, Títí Kan Àwọn Tó Ti Lé ní Àádọ́rin Ọdún | task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 9 | train |
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form. The output ... | Farah bẹ̀ẹ̀rẹ̀ sí ní fakọyọ nínú ọ̀kan-ò-jọ̀kan eré-ìje láti ìgbà tí ó ti gba àmì-ẹ̀yẹ góòlù nígbà méjì ọ̀tọ̀ọ̀tọ̀ lọ́dún 2012 àti ọdún 2016 nínú ìdíje Olympic.
| task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 5 | train |
Definition: In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form.... | Àmọ́, ilé àwọn ará wa méjìdínlógójì (38) àti Gbọ̀ngàn Ìjọba méjì ló bà jẹ́. | task1619_menyo20k_mt_en_yo_translation | NIv2 | zs_opt | 2 | train |
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form. The output ... | Ń gbìyànjú láti tún sopọ̀…
| task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 7 | train |
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form. The output ... | Output: Ẹbọ díẹ̀, oògùn díẹ̀, ní ń gba aláìkú là.
| task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 2 | test |
In this task, you are given a sentence in the English language from the various articles. Your task is to translate the given English sentence into the Yoruba language. Please bear in mind the following guidelines while doing the translation: 1) Generated output should have natural language and formal form. The output ... | Ẹní máa jẹ oyin inú àpáta kìí wo ẹnu àáké.
| task1619_menyo20k_mt_en_yo_translation | NIv2 | fs_opt | 1 | validation |
You will be given a definition of a task first, then some input of the task.
Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
I had seen it before, those fuzzy, furry leaves and stalks, with the pretty, star-pointed purple flowers, but up until that moment tha... | Who told the author that the plants were borage? | task886_quail_question_generation | NIv2 | zs_opt | 1 | train |
Detailed Instructions: Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
See one example below:
Problem: I really struggle to feel bad for people who actively choose to be miserable and manipulative. I'm dorky and like to use little proverbs all the time. One of... | Who gave diplomacy another chance to succeed? | task886_quail_question_generation | NIv2 | fs_opt | 4 | train |
Detailed Instructions: Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
Problem:His eyes were open and his head bobbed around at an impossible angle. He was sitting in about forty feet of water, stone dead, one arm pinned between the rocks. As best I could tell... | Who got coke out of the cooler? | task886_quail_question_generation | NIv2 | zs_opt | 8 | train |
Teacher:Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
Teacher: Now, understand the problem? Solve this instance: U.S. President-elect Donald Trump's choice to lead the Department of Homeland Security, retired Marine General John Kelly, is one of the U.S. mil... | Who was succeeded by Kelly at U.S Southern Command? | task886_quail_question_generation | NIv2 | zs_opt | 6 | train |
You will be given a definition of a task first, then some input of the task.
Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
I was fencing wire at Flat Broke Acres and trying to tighten up the wire a bit. I lost the grip of the fencing wire and the pliers sma... | Who hit themselves in the mouth? | task886_quail_question_generation | NIv2 | zs_opt | 1 | train |
Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
--------
Question: I am currently waiting for peer reviews of two books I've worked on: one sole-authored, one co-authored. We don't talk much about the experience of waiting for reviews, and it's not something t... | Who found another doctor that treated the narrator like they were human?
| task886_quail_question_generation | NIv2 | fs_opt | 7 | train |
Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
Q: A confession: I quietly love flying. This year, I've done 163,581 miles of it.
I love that when you fly a lot, the airport social media staff say 'hello' on Twitter when you arrive and the cabin crew on your h... | Who lives in Melbourne? | task886_quail_question_generation | NIv2 | zs_opt | 4 | train |
Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
The drive up to Rick's place in the hills always made me sick. Just after he bought the house with his ill gotten gains from his band's over-hyped, over-marketed, and over-bought sophomore Disc, he drove me out ... | Who was gorgeous by some standards? | task886_quail_question_generation | NIv2 | zs_opt | 0 | train |
Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
One example is below.
Q: I really struggle to feel bad for people who actively choose to be miserable and manipulative. I'm dorky and like to use little proverbs all the time. One of my favorites is this: "you ca... | Who had to make a decision? | task886_quail_question_generation | NIv2 | fs_opt | 9 | test |
Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
[Q]: President Donald Trump and North Korean leader Kim Jong Un made history with their summit meeting in Singapore. But beyond the handshakes, casual strolls and shared asides, many analysts and experts are alr... | Who was a southern baptist?
| task886_quail_question_generation | NIv2 | fs_opt | 5 | validation |
Detailed Instructions: In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering the question. Here is the Alphabetical list of part-of-speech tags used in this task: CC: Coordinating conjunction, CD: Cardinal number, DT: Dete... | WP | task382_hybridqa_answer_generation | NIv2 | fs_opt | 4 | train |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | NN
| task382_hybridqa_answer_generation | NIv2 | fs_opt | 5 | train |
Q: In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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: Existent... | NN | task382_hybridqa_answer_generation | NIv2 | zs_opt | 7 | train |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | RBS | task382_hybridqa_answer_generation | NIv2 | fs_opt | 6 | train |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | VBD | task382_hybridqa_answer_generation | NIv2 | fs_opt | 9 | train |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | DT | task382_hybridqa_answer_generation | NIv2 | fs_opt | 9 | train |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | VBD
| task382_hybridqa_answer_generation | NIv2 | fs_opt | 0 | train |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | NN
| task382_hybridqa_answer_generation | NIv2 | fs_opt | 3 | train |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | NN
| task382_hybridqa_answer_generation | NIv2 | fs_opt | 1 | test |
In this task, you will be presented with a question about part-of-speech tag of a word in the question. You should write the required POS tag answering 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... | Solution: DT | task382_hybridqa_answer_generation | NIv2 | fs_opt | 5 | validation |
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. Please answer with "Contradiction", "Neutral", or "Entailment".
Input: Consider Input: Premise: Intermountai... | Output: Entailment
| task1386_anli_r2_entailment | NIv2 | fs_opt | 2 | train |
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. Please answer with "Contradiction", "Neutral", or "Entailment".
Example Input: Premise: Dobrynya Nikitich an... | Neutral
| task1386_anli_r2_entailment | NIv2 | fs_opt | 3 | train |
You will be given a definition of a task first, then some input of the task.
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. Please answer with "Contradictio... | Neutral | task1386_anli_r2_entailment | NIv2 | zs_opt | 1 | train |
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. Please answer with "Contradictio... | Neutral | task1386_anli_r2_entailment | NIv2 | fs_opt | 1 | train |
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. Please answer with "Contradiction", "Neutral", or "Entailment".
Let me give you an example: Premise: The Was... | Neutral | task1386_anli_r2_entailment | NIv2 | fs_opt | 8 | train |
instruction:
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. Please answer with "Contradiction", "Neutral", or "Entailment".
question:
Premise: Anti-Dühring ... | Contradiction
| task1386_anli_r2_entailment | NIv2 | fs_opt | 9 | train |
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. Please answer with "Contradiction", "Neutral", or "Entailment".
Q: Premise: Communal riots occurred in Bihar ... | Neutral | task1386_anli_r2_entailment | NIv2 | zs_opt | 4 | train |
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. Please answer with "Contradiction", "Neutral", or "Entailment".
[Q]: Premise: The 1938 Montana Grizzlies foo... | Entailment
| task1386_anli_r2_entailment | NIv2 | fs_opt | 5 | train |
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. Please answer with "Contradiction", "Neutral", or "Entailment".
Example Input: Premise: "The Orange and the ... | Neutral
| task1386_anli_r2_entailment | NIv2 | fs_opt | 3 | test |
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. Please answer with "Contradiction", "Neutral", or "Entailment".
[Q]: Premise: Bridge Mountain is a mountain ... | Contradiction
| task1386_anli_r2_entailment | NIv2 | fs_opt | 5 | validation |
Detailed Instructions: In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Q: [[-22, -17], [41, 27], [... | [374, 1107, -13068, 3900, -9133488] | task371_synthetic_product_of_list | NIv2 | zs_opt | 9 | train |
Detailed Instructions: In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Q: [[-9, -36, -4], [-14, 33... | [-1296, 9240, -120, 31465, -1440, -1692, -195360, -11867310] | task371_synthetic_product_of_list | NIv2 | zs_opt | 9 | train |
In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Example: [[5, 1, 2, 7], [0, 4, 6, 6], [7, 8, 10, 3... | Solution: [1044, 0, -49248, 59682, -12600, -4554300] | task371_synthetic_product_of_list | NIv2 | fs_opt | 5 | train |
Detailed Instructions: In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Problem:[[20, 45, 31], [-35... | [27900, 18655, 765600, 902, 759240, 130416, -29, 7812, -262080, -20533500] | task371_synthetic_product_of_list | NIv2 | zs_opt | 8 | train |
Detailed Instructions: In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Q: [[16, -13, -6, -6], [-18... | [-7488, 7783776, -28952000] | task371_synthetic_product_of_list | NIv2 | zs_opt | 9 | train |
Teacher:In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Teacher: Now, understand the problem? Solv... | [11571840, 528] | task371_synthetic_product_of_list | NIv2 | zs_opt | 6 | train |
In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
[EX Q]: [[-41, -29], [26, 48, 28, 43, -46]]
[EX A... | [396, -9840, -224640, 154, -11268720, 12672, -574560, -50048, 0, -947520]
| task371_synthetic_product_of_list | NIv2 | fs_opt | 6 | train |
Given the task definition and input, reply with output. In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input ... | [1620, -1519] | task371_synthetic_product_of_list | NIv2 | zs_opt | 5 | train |
In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Q: [[33, 29], [-49, -11, -13, 4, -20]]
A: | [957, 560560] | task371_synthetic_product_of_list | NIv2 | zs_opt | 4 | test |
Instructions: In this task you will be given a list of lists, of numbers. For every inner list, you should multiply every number in that list and put the results in your answer. The output should be a list of numbers with the same length as the number of the lists in the input list.
Input: [[-30, -28, -39], [50, -30], ... | [-32760, -1500, 29440, -130, -1487808, 15686400, 65366, -20160] | task371_synthetic_product_of_list | NIv2 | zs_opt | 3 | validation |
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