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You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Example input: How many miles is 43560 ?
What is the national currency of Albania ?
What is the status of the draft today in ... | What are some advantages of useing coal as a energy form ? | task674_google_wellformed_query_sentence_generation | NIv2 | fs_opt | 3 | train |
Teacher:You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Teacher: Now, understand the problem? Solve this instance: How is it from the Sun to Venus ?
How many landforms are in... | How is it from the Sun to Venus ? | task674_google_wellformed_query_sentence_generation | NIv2 | zs_opt | 6 | train |
You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Ex Input:
What problems did the Aztecs face ?
When did madagascar win it 's independence ?
What is the population of trinidad... | What is mean by an exothermic and an exothermic reaction ?
| task674_google_wellformed_query_sentence_generation | NIv2 | fs_opt | 1 | train |
Detailed Instructions: You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Q: How do rocks get identified ?
How do you deal with annoying little brothers ?
How many series are th... | The country north of France ? | task674_google_wellformed_query_sentence_generation | NIv2 | zs_opt | 9 | train |
You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
What causes opacity ?
Are static shocks more severe in the summer or winter ?
Lever is akind of simple machine ?
How much mon... | Lever is akind of simple machine ? | task674_google_wellformed_query_sentence_generation | NIv2 | zs_opt | 0 | train |
You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Ex Input:
What is the sound quality of the oboe ?
Where did Roald Dahl live in his teenaged years ?
Huge flowers that start w... | Comparative genome analysis of mesophiles ?
| task674_google_wellformed_query_sentence_generation | NIv2 | fs_opt | 1 | train |
Detailed Instructions: You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Q: How many miles between cleveland and cincinnati ohio ?
What countries are not leting women have no r... | What countries are not leting women have no right today ? | task674_google_wellformed_query_sentence_generation | NIv2 | zs_opt | 9 | train |
Q: You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
How far between Heathrow and Toronto ?
Why was oliver twist a poor boy ?
What are the 5 positions in a basketball game ?
Wh... | How far between Heathrow and Toronto ? | task674_google_wellformed_query_sentence_generation | NIv2 | zs_opt | 7 | train |
You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Example: How many miles is 43560 ?
What is the national currency of Albania ?
What is the status of the draft today in US ?
Wh... | Solution: One difference between the manorial and feudal systems is ? | task674_google_wellformed_query_sentence_generation | NIv2 | fs_opt | 5 | test |
Teacher:You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Teacher: Now, understand the problem? Solve this instance: How do you adjust the headlights on a 2004 Hyundai Elantra ... | How do butterflies protect there babies ? | task674_google_wellformed_query_sentence_generation | NIv2 | zs_opt | 6 | validation |
Definition: The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking... | cerca "big woodys". | task173_spl_translation_en_it | NIv2 | zs_opt | 2 | train |
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloqu... | qual è la valutazione di quel " mcdonald ' "? | task173_spl_translation_en_it | NIv2 | zs_opt | 0 | train |
Detailed Instructions: The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *N... | mostrami ristoranti presso " west suburbs ". | task173_spl_translation_en_it | NIv2 | zs_opt | 8 | train |
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloqu... | mostrami i ristoranti "mexican" con un punteggio di almeno 7 stelle.
| task173_spl_translation_en_it | NIv2 | fs_opt | 0 | train |
Definition: The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking... | mostrami tutta la recensione scritta da "alex smith" sui ristoranti "chinese". | task173_spl_translation_en_it | NIv2 | zs_opt | 2 | train |
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloqu... | trova ristoranti con più di 4 recensioni. | task173_spl_translation_en_it | NIv2 | zs_opt | 0 | train |
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloqu... | qual è il ristorante " italian " più vicino con una valutazione di almeno 7 stelle? | task173_spl_translation_en_it | NIv2 | zs_opt | 4 | train |
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloqu... | forniscimi il numero di telefono del ristorante "mexican" più vicino nell'area di codice postale "93312". | task173_spl_translation_en_it | NIv2 | zs_opt | 0 | 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.
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are l... | cerca tutte le recensioni di " john oyster ". | task173_spl_translation_en_it | NIv2 | fs_opt | 0 | test |
Part 1. Definition
The provided file includes inquiries about restaurants, and we ask you to translate those to the Italian language. Please bear in mind the following guidlines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* ... | mostrami il numero di telefono di un ristorante "mexican". | task173_spl_translation_en_it | NIv2 | fs_opt | 7 | validation |
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
[Q]: Kyle: hi, how is the d... | False
| task1573_samsum_classification | NIv2 | fs_opt | 5 | train |
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
Maggie: Fantastic pics!, Ju... | False | task1573_samsum_classification | NIv2 | zs_opt | 0 | train |
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
Ex Input:
Paul: I think the... | False
| task1573_samsum_classification | NIv2 | fs_opt | 1 | train |
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
Q: Woodie: How much more Ami... | False | task1573_samsum_classification | NIv2 | zs_opt | 4 | train |
Detailed Instructions: In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
Proble... | False | task1573_samsum_classification | NIv2 | zs_opt | 8 | train |
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
Example input: Noah: When a... | True | task1573_samsum_classification | NIv2 | fs_opt | 3 | train |
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
Ryan: 1234, Ryan: :D
True
... | False
| task1573_samsum_classification | NIv2 | fs_opt | 0 | train |
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
--------
Question: Mary: A d... | True
| task1573_samsum_classification | NIv2 | fs_opt | 7 | train |
instruction:
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two sentences are spoken by two different people.
question:
Maggi... | True
| task1573_samsum_classification | NIv2 | fs_opt | 9 | test |
You will be given a definition of a task first, then some input of the task.
In this task, you are given two sentences taken from a conversation, and your job is to classify whether these given sentences are sequential or not. We will mark the given sentence pair as 'True' if it's sequential, otherwise 'False'. The two... | True | task1573_samsum_classification | NIv2 | zs_opt | 1 | validation |
Definition: In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Input: a complex tale of labor and strife, told with efficiency . After "L'Ass... | POS | task476_cls_english_books_classification | NIv2 | zs_opt | 2 | train |
In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Protector has always been entertaining . I have always enjoyed the older books by Larry N... | POS | task476_cls_english_books_classification | NIv2 | zs_opt | 0 | train |
Teacher: In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Teacher: Now, understand the problem? If you are still confused, see the followin... | NEG | task476_cls_english_books_classification | NIv2 | fs_opt | 2 | train |
In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
So You Wanna Start a Revolution? . Common Sense is a must read for all citizens of the US... | NEG
| task476_cls_english_books_classification | NIv2 | fs_opt | 0 | train |
TASK DEFINITION: In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
PROBLEM: Amazing Reading Experience . I first borrowed this book from the... | NEG
| task476_cls_english_books_classification | NIv2 | fs_opt | 8 | train |
In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
and the beat goes on... and the beat goes on... . There are several books out there fille... | POS | task476_cls_english_books_classification | NIv2 | zs_opt | 0 | train |
In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
[Q]: totally suprising (in a good way) . this book was totally awesome! i mean people thi... | NEG
| task476_cls_english_books_classification | NIv2 | fs_opt | 5 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Buyer Beware... | NEG | task476_cls_english_books_classification | NIv2 | zs_opt | 1 | 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 books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentim... | POS | task476_cls_english_books_classification | NIv2 | fs_opt | 0 | test |
In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Example Input: A fun take on an old song . Watch out, this book is addictive. My 14 mont... | POS
| task476_cls_english_books_classification | NIv2 | fs_opt | 3 | validation |
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
--------
Question: name[Loch Fyne], eatType[re... | Alimentum is a children friendly fast food outlet in the city centre, with a high price range.
| task957_e2e_nlg_text_generation_generate | NIv2 | fs_opt | 7 | train |
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
Input: name[The Twenty Two], eatTy... | The Twenty Two Pub in the City Centre next to Café Sicilia is rated highly. | task957_e2e_nlg_text_generation_generate | NIv2 | zs_opt | 2 | train |
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
name[The Eagle], eatType[coffee shop], food[I... | In the Riverside area there is an Italian food venue named The Phoenix. It is in the high price range and has an average customer rating.
| task957_e2e_nlg_text_generation_generate | NIv2 | fs_opt | 0 | train |
You will be given a definition of a task first, then some input of the task.
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all t... | In spite of a low customer rating, The Golden Curry and a wonderful choice for family friendly Japanese cuisine. | task957_e2e_nlg_text_generation_generate | NIv2 | zs_opt | 1 | train |
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
--------
Question: name[The Plough], eatType[p... | Strada is a pub which serves Chinese food is located near Yippee Noodle Bar, and has a high customer rating of 5 out of 5.
| task957_e2e_nlg_text_generation_generate | NIv2 | fs_opt | 7 | 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, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and g... | Loch Fyne is a moderately priced restaurant offering Italian food while being kid friendly. | task957_e2e_nlg_text_generation_generate | NIv2 | fs_opt | 0 | train |
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
Example input: name[Aromi], eatType[restauran... | The Rice Boat is a restaurant of average rating, is offering Chinese food and is child friendly. It is located at a riverside. | task957_e2e_nlg_text_generation_generate | NIv2 | fs_opt | 3 | train |
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
Q: name[Aromi], eatType[coffee shop], food[Jap... | A Japanese coffee shop Aromi is in the riverside area that is children friendly with high customer rating | task957_e2e_nlg_text_generation_generate | NIv2 | zs_opt | 4 | train |
Detailed Instructions: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
Q: name[Browns Cambridg... | Browns Cambridge is a restaurant that serves expensive Japanese food. | task957_e2e_nlg_text_generation_generate | NIv2 | zs_opt | 9 | test |
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
Let me give you an example: name[Aromi], eatT... | The Phoenix has a customer rating of 1 out of 5. It serves Italian food and is in the riverside area. | task957_e2e_nlg_text_generation_generate | NIv2 | fs_opt | 8 | validation |
Q: In this task you are given a question. You need to generate an answer to the question.
Question:What amateur rowing club based at Henley on Thames, England, was founded in 1818?
A: | Henley Rowing club | task1564_triviaqa_answer_generation | NIv2 | zs_opt | 7 | train |
In this task you are given a question. You need to generate an answer to the question.
--------
Question: Question:With what is FIFA usually associated?
Answer: Football
Question: Question: Which Europeans have been proved to have reached North America before Christopher Columbus?
Answer: Viking
Question: Questio... | Sherif Ali
| task1564_triviaqa_answer_generation | NIv2 | fs_opt | 7 | 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 question. You need to generate an answer to the question.
Question:Who was the man behind The Chipmunks?
Solution: David Seville
Why? David Seville was the man behind th... | vodoo | task1564_triviaqa_answer_generation | NIv2 | fs_opt | 0 | train |
In this task you are given a question. You need to generate an answer to the question.
--------
Question: Question:Horatio was a legendary Roman hero who defended a bridge against which army?
Answer: Tiber
Question: Question:Dishes prepared with spinach can be referred to as what?
Answer: Spinach
Question: Questi... | Bloody Mary
| task1564_triviaqa_answer_generation | NIv2 | fs_opt | 7 | train |
In this task you are given a question. You need to generate an answer to the question.
Example: Question:Who was the man behind The Chipmunks?
Example solution: David Seville
Example explanation: David Seville was the man behind the Chipmunks.
Problem: Question:Michael Phelps who during the Summer Olympics 2012 brough... | Solution: USA | task1564_triviaqa_answer_generation | NIv2 | fs_opt | 5 | train |
Teacher:In this task you are given a question. You need to generate an answer to the question.
Teacher: Now, understand the problem? Solve this instance: Question:What is the name of the A1 Pacific steam locomotive which was completed in 2009 and is the first of its kind built for over 50 years?
Student: | tornado | task1564_triviaqa_answer_generation | NIv2 | zs_opt | 6 | train |
In this task you are given a question. You need to generate an answer to the question.
Question:What island would you come to first if you travelled due east from Bangladesh?
Bjørnøya
Question:What is the only county in the USA to border 5 counties from 5 different states : Baca County, Colorado; Morton County, Kansa... | japan
| task1564_triviaqa_answer_generation | NIv2 | fs_opt | 0 | train |
instruction:
In this task you are given a question. You need to generate an answer to the question.
question:
Question:If the Staten Island Ferry is to New York, the Star Ferry that was originally called the Kowloon Ferry Company is to what city?
answer:
New York
question:
Question:What is the US term for for an area... | dumplings
| task1564_triviaqa_answer_generation | NIv2 | fs_opt | 9 | train |
You will be given a definition of a task first, then some input of the task.
In this task you are given a question. You need to generate an answer to the question.
Question:What Scottish city is at the confluence of the rivers Dee and Don?
Output: | Aberdeen | task1564_triviaqa_answer_generation | NIv2 | zs_opt | 1 | test |
Detailed Instructions: In this task you are given a question. You need to generate an answer to the question.
Problem:Question:Which Japanese island that has its capital at Sapporo is the traditional home of the Ainu people?
Solution: | Sapporo | task1564_triviaqa_answer_generation | NIv2 | zs_opt | 8 | validation |
You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The output should... | No | task383_matres_classification | NIv2 | zs_opt | 4 | train |
Given the task definition and input, reply with output. You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or ... | No | task383_matres_classification | NIv2 | zs_opt | 5 | train |
Detailed Instructions: You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the fu... | Yes | task383_matres_classification | NIv2 | zs_opt | 8 | train |
You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The output should... | No | task383_matres_classification | NIv2 | zs_opt | 0 | 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, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, ... | Yes | task383_matres_classification | NIv2 | zs_opt | 1 | train |
You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The output should... | No
| task383_matres_classification | NIv2 | fs_opt | 5 | train |
Instructions: You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The... | Yes | task383_matres_classification | NIv2 | zs_opt | 3 | train |
You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The output should... | No
****
| task383_matres_classification | NIv2 | fs_opt | 4 | train |
You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The output should... | No
| task383_matres_classification | NIv2 | fs_opt | 0 | test |
You will be given a context and a verb separated with a newline character, and you have to answer if the given verb can be anchored in time or not. We say a verb can be anchored in the real timeline if and only if a verb happened in the past, is happening now, or is guaranteed to happen in the future. The output should... | Yes
| task383_matres_classification | NIv2 | fs_opt | 6 | validation |
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
Example Input: all
Example Output: tall
Example Input: field
Example Output: yield
Example Input: salt
Example Output: | vault
| task183_rhyme_generation | NIv2 | fs_opt | 3 | train |
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
Q: suffix
A: | No | task183_rhyme_generation | NIv2 | zs_opt | 4 | train |
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
Q: spring
A: | swing | task183_rhyme_generation | NIv2 | zs_opt | 4 | train |
Part 1. Definition
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
Part 2. Example
difficult
Answer: No
Explanation: The word difficult has no natural English rhymes and so the model outputs No as specified in the instructions.
Part 3. Exercise
shall
Answer... | al | task183_rhyme_generation | NIv2 | fs_opt | 7 | train |
TASK DEFINITION: Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
PROBLEM: mind
SOLUTION: find
PROBLEM: equate
SOLUTION: strait
PROBLEM: distant
SOLUTION: | persistent
| task183_rhyme_generation | NIv2 | fs_opt | 8 | train |
You will be given a definition of a task first, then some input of the task.
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
paragraph
Output: | falstaff | task183_rhyme_generation | NIv2 | zs_opt | 1 | train |
Definition: Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
Input: any
Output: | lenny | task183_rhyme_generation | NIv2 | zs_opt | 2 | train |
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
Let me give you an example: difficult
The answer to this example can be: No
Here is why: The word difficult has no natural English rhymes and so the model outputs No as specified in the instructions.
OK. sol... | mission | task183_rhyme_generation | NIv2 | fs_opt | 8 | train |
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
Ex Input:
morning
Ex Output:
warning
Ex Input:
fruit
Ex Output:
hoot
Ex Input:
why
Ex Output:
| jai
| task183_rhyme_generation | NIv2 | fs_opt | 1 | test |
Given an input word generate a word that rhymes exactly with the input word. If not rhyme is found return "No"
One example: difficult
Solution is here: No
Explanation: The word difficult has no natural English rhymes and so the model outputs No as specified in the instructions.
Now, solve this: dad
Solution: | chad | task183_rhyme_generation | NIv2 | fs_opt | 6 | validation |
Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Ex Input:
它位于Shawnee镇，毗邻艾伦县的Duchouquet镇。
Ex Output:
It is located in Shawnee Township and is adjacent to Duchouquet Township in Allen County .
Ex Input... | Sir James married , in 1872 , John Nairne Forman ( d. 20 December 1929 ) , daughter of Helen Margaret of Staffa , WS .
| task807_pawsx_chinese_english_translation | NIv2 | fs_opt | 1 | train |
Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Example: 1975年的NBA赛季 - 76赛季是全美篮球协会的第30个赛季。
Example solution: The 1975 -- 76 season of the National Basketball Association was the 30th season of the NBA .... | Solution: Born on November 1 , 1986 , Ashley is a contemporary dancer from Los Angeles who was originally raised in Arizona . | task807_pawsx_chinese_english_translation | NIv2 | fs_opt | 5 | train |
Definition: Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Input: 轻小说是由Dojyomaru写的，由Fuyuyuki演绎并由Overlap Bunko出版。
Output: | The light novels are written by Dojyomaru and illustrated by Fuyuyuki , and are published by Overlap Bunko . | task807_pawsx_chinese_english_translation | NIv2 | zs_opt | 2 | train |
instruction:
Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
question:
他还出演了音乐电影，后来出演了喜剧角色。
answer:
He also appeared in musical films and later in life , in comedic roles .
question:
在罗杰去世后，他的儿子 - 林肯伯爵... | She plays for Naisten Liiga of the Åland United .
| task807_pawsx_chinese_english_translation | NIv2 | fs_opt | 9 | train |
Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Q: 1819年8月31日，沃斯通克拉夫特号在悉尼船上抵达格林纳达。
A: | Wollstonecraft arrived on August 31 , 1819 on board the ship " Sydney " in Grenada . | task807_pawsx_chinese_english_translation | NIv2 | zs_opt | 4 | train |
TASK DEFINITION: Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
PROBLEM: SDUU目前在斯德哥尔摩，哥德堡，哈尔姆斯塔德，卡尔马，斯科讷，厄勒布鲁，于默奥，谢莱夫特奥和皮特奥设有分支机构。
SOLUTION: SDUU currently has local branches in Skåne , Örebro , Umeå ,... | During the five days of the journey , he brought some books about Elba which he studied from Fontainebleau .
| task807_pawsx_chinese_english_translation | NIv2 | fs_opt | 8 | train |
Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Example input: 1975年的NBA赛季 - 76赛季是全美篮球协会的第30个赛季。
Example output: The 1975 -- 76 season of the National Basketball Association was the 30th season of the ... | The Sâmbăta river is a tributary of the River Piatra Caprei in Romania . | task807_pawsx_chinese_english_translation | NIv2 | fs_opt | 3 | train |
Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Example Input: 两年后，伯德于1970年与布朗重聚。
Example Output: After two years , Byrd reunited with Brown in 1970 .
Example Input: Hidalgo出生于塞维利亚，效力于巴达霍斯和塞尔维德维戈。
Exam... | The Italian St. Giovanni Bosco Church is named after St. John Bosco .
| task807_pawsx_chinese_english_translation | NIv2 | fs_opt | 3 | train |
Detailed Instructions: Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Q: 克罗克从密西西比州的纳奇兹搬到康科迪亚教区的总部维达利亚，并在黑河区穿越了下瓦希塔。
A: | Crocker moved from Natchez , Mississippi to Vidalia , the seat of Concordia Parish , and crossed toward the lower Ouachita in the section called the Black River . | task807_pawsx_chinese_english_translation | NIv2 | zs_opt | 9 | test |
Given the task definition and input, reply with output. Given a sentence in Chinese, provide an equivalent paraphrased translation in English that retains the same meaning both through the translation and the paraphrase.
Togdheer（索马里'Wabi Togdheer'）是索马里兰东部Togdheer河地区的一条季节性河流。
| Togdheer ( Somali " Wabi Togdheer " ) is a seasonal river in the Togdheer River region of eastern Somaliland . | task807_pawsx_chinese_english_translation | NIv2 | zs_opt | 5 | validation |
Definition: In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
Input: the only thing worse than watching a bad movie is realizing that the film had a lot of potential and could 've been effective .
such is the case with _ urban legend _ , the new horror film from f... | N | task1361_movierationales_classification | NIv2 | zs_opt | 2 | train |
In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
Example: plot : two teen couples go to a church party , drink and then drive .
they get into an accident .
one of the guys dies , but his girlfriend continues to see him in her life , and has nightmares .
what 's t... | Solution: N | task1361_movierationales_classification | NIv2 | fs_opt | 5 | train |
In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
jacques tati 's 1953 classic " les
vacances
de m . hulot " ( also known as " mr .
hulot 's vacation , " in english ) ought to be the textbook on how to do non ?
dialogue comedy in film .
the characters hardly ever... | P
| task1361_movierationales_classification | NIv2 | fs_opt | 0 | train |
instruction:
In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
question:
sometimes , when i decide to write a short story or a poem , i think of a title first , and then think of a subject to go with it .
it seems that the makers of disturbing behavior had a simil... | N
| task1361_movierationales_classification | NIv2 | fs_opt | 9 | 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 must classify if a given review is positive/negative, indicating your answer as P or N.
plot : two teen couples go to a church party , drink and then drive .
they get into an accid... | P | task1361_movierationales_classification | NIv2 | fs_opt | 0 | train |
In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
susan granger 's review of " session 9 " ( usa films ) sometimes you just get more than your bargained for . . .
like when boston - based hazmat elimination , run by scottish actor peter mullan and his trusty assi... | N | task1361_movierationales_classification | NIv2 | zs_opt | 0 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
annie wilson ( cate blanchett ) , a widow who struggles to raise her children in a small town in georgia is asked for help by local auth... | N | task1361_movierationales_classification | NIv2 | zs_opt | 1 | train |
Detailed Instructions: In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
Q: " being john malkovich " is the type of film we need to see more .
today 's films are either blockbusters that entertain us with tiresome formulas , or those that have similar themes .
mal... | P | task1361_movierationales_classification | NIv2 | zs_opt | 9 | train |
In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
--------
Question: gothic murder - mystery yarns are not a new conceit .
in fact , they 've been around in books and on film for many , many years .
without the proper handling , they come off as old - fashioned , ... | P
| task1361_movierationales_classification | NIv2 | fs_opt | 7 | test |
Detailed Instructions: In this task, you must classify if a given review is positive/negative, indicating your answer as P or N.
Problem:' bicentennial man ' is a family film without any external motive with the exception of providing the minimum dose of entertainment .
chris columbus , the director who gave you " mrs ... | N | task1361_movierationales_classification | NIv2 | zs_opt | 8 | validation |
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