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Please answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "GPS Nice app 🎅🎃👻😃😁🐰🐹🐺🐙"
Answer: | 3 | app_reviews_convert_to_rating | P3 | zs_noopt | 9 | train |
Please answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Loved it Best learning app ever."
A: | 5 | app_reviews_convert_to_rating | P3 | zs_opt | 8 | train |
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Nice Easy"
++++++++
Answer: 5
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Ok!"
++++++++
Answer: 5
Pl... | 5 | app_reviews_convert_to_rating | P3 | fs_opt | 6 | train |
Answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "hoooo"
Answer: | 5 | app_reviews_convert_to_rating | P3 | zs_noopt | 5 | train |
Please answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Add silent mode Clicking sound mute option should be add"
Answer: | 3 | app_reviews_convert_to_rating | P3 | zs_opt | 9 | train |
Answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Best"
Answer: | 5 | app_reviews_convert_to_rating | P3 | zs_noopt | 5 | train |
On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "No more running to the pc Love this app it does what I need it to do search repos for stuff I like to see or hear. Hope soon if I'm not mistaken an ability to use hand gestures instead of arrow keys would be re... | 1 | app_reviews_convert_to_rating | P3 | fs_opt | 1 | train |
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Perfect"
++++++++
Answer: 5
Problem: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "My Google account signs into Google"
A: ... | 5 | app_reviews_convert_to_rating | P3 | fs_opt | 1 | train |
input: Please answer the following: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "S7 Great"
++++++++++
output: 3
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Nice app"
+... | 1 | app_reviews_convert_to_rating | P3 | fs_opt | 8 | test |
Problem: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Good"
A: 5
Problem: Given the question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Bbbb Mmmm"
++++++++++++++++++++++++++++++++
The ... | 5 | app_reviews_convert_to_rating | P3 | fs_opt | 3 | validation |
Instructions: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Input: concept: Costa Rica question: what language do people speak in costa rica?
Output: | ['Spanish Language'] | task1601_webquestions_answer_generation | NIv2 | zs_opt | 3 | train |
Detailed Instructions: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Problem:concept: Indonesia question: what language do they speak in indonesia?
Solution: | ['Javanese Language', 'Malay Language', 'Sunda Language', 'English Language', 'Bali Language', 'Indonesian Language', 'Batak Language', 'Tobelo Language', 'Dutch Language', 'Madura Language'] | task1601_webquestions_answer_generation | NIv2 | zs_opt | 8 | train |
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
One example: concept: Selena Gomez question: what city was selena gomez born in?
Solution is here: New York City
Explanation: The answer is correct based on ... | ['Nicolas Sarkozy'] | task1601_webquestions_answer_generation | NIv2 | fs_opt | 6 | train |
Detailed Instructions: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Problem:concept: Chris Colfer question: what movies has chris colfer been in?
Solution: | ['8', 'Russel Fish: The Sausage and Eggs Incident', 'Glee Encore', 'Struck by Lightning', 'Glee: The 3D Concert Movie'] | task1601_webquestions_answer_generation | NIv2 | zs_opt | 8 | train |
You will be given a definition of a task first, then some input of the task.
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
concept: Michigan question: who won the governor election in michigan?
Output... | ['Rick Snyder'] | task1601_webquestions_answer_generation | NIv2 | zs_opt | 1 | train |
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Ex Input:
concept: Lola Bunny question: who plays lola bunny in the looney tunes show?
Ex Output:
['Britt McKillip', 'Kath Soucie']
Ex Input:
concept: ... | ['St. Francis of Assisi Catholic School']
| task1601_webquestions_answer_generation | NIv2 | fs_opt | 1 | train |
TASK DEFINITION: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
PROBLEM: concept: Harley Quinn question: who should play harley quinn?
SOLUTION: ['Arleen Sorkin', 'Mia Sara', 'Hynden Walch']
PROBLEM: ... | ['Him/Herself']
| task1601_webquestions_answer_generation | NIv2 | fs_opt | 8 | train |
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Example: concept: Selena Gomez question: what city was selena gomez born in?
Example solution: New York City
Example explanation: The answer is correct based... | Solution: ['Icelandic Language'] | task1601_webquestions_answer_generation | NIv2 | fs_opt | 5 | 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.
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
concept: Selena Gomez question: wha... | ['Parliamentary system', 'Unitary state', 'Constitutional monarchy'] | task1601_webquestions_answer_generation | NIv2 | fs_opt | 0 | test |
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Example: concept: Selena Gomez question: what city was selena gomez born in?
Example solution: New York City
Example explanation: The answer is correct based... | Solution: ['Presbyterianism', 'Baptists', 'Catholicism'] | task1601_webquestions_answer_generation | NIv2 | fs_opt | 5 | validation |
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Place all dry ingredients in a large mixing bowl and stir together with a wire w... | White Cake Mix, All-purpose, Sugar, Salt, Water, Vegetable Oil, Vanilla, Almond Extract, Sour Cream, Egg Whites | task571_recipe_nlg_ner_generation | NIv2 | zs_opt | 5 | train |
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Grill chicken breast. Prepare rice as directed. Add vegetables. Saut mushrooms a... | chicken breast halves, Uncle Ben, white cheese, mixed vegetables, fresh mushrooms, onions | task571_recipe_nlg_ner_generation | NIv2 | zs_opt | 5 | train |
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Let me give you an example: Preheat oven to 375 degrees., Boil syrup, sugar and shortening over medium heat, stirring constantly., Remov... | deli, pastry sheets, mustard, Mozzarella, egg | task571_recipe_nlg_ner_generation | NIv2 | fs_opt | 8 | train |
Q: In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
In 12-inch nonstick skillet, heat Olive Oil over medium heat and cook garlic paste, stirring occasionally, 2 minutes or until slightly... | Olive Oil, garlic, Tomato, shrimp, green olives, pepperoncini, parsley, linguine | task571_recipe_nlg_ner_generation | NIv2 | zs_opt | 7 | train |
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
In a large pot, melt the butter over moderately low heat. Add the onion; cook, s... | butter, onion, garlic, broccoli, boiling potatoes, chicken broth, water, salt, fresh-ground black pepper, Parmesan | task571_recipe_nlg_ner_generation | NIv2 | zs_opt | 5 | train |
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
--------
Question: Toss broccoli, raisins, onion, nuts, and bacon., In separate bowl, mix sugar, vinegar and mayonnaise., Pour mixture ov... | Vegetable cooking spray, pork tenderloin, purple onion, mango, Madeira wine, lime juice, onion rolls
| task571_recipe_nlg_ner_generation | NIv2 | fs_opt | 7 | train |
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Q: Cream sugar and cream cheese together., Stir in Cool Whip. Add nuts, bananas, pineapple and strawberries; mix well. Refrigerate.
A: | cream cheese, sugar, banana slices, pecan pieces, pineapple, frozen strawberries | task571_recipe_nlg_ner_generation | NIv2 | zs_opt | 4 | train |
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
[EX Q]: Preheat oven to 325F Line a 13x9 inch baking pan with foil., Brush foil with 1 tablespoon melted butter; set aside., In a large ... | browns, cream of chicken soup, cream of mushroom soup, sour cream, onion, cheese
| task571_recipe_nlg_ner_generation | NIv2 | fs_opt | 6 | train |
Detailed Instructions: In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Problem:Heat 4 Tbsp., butter in heavy large saucepan over medium heat., Add in onion and garlic; saute/fry till li... | butter, onion, garlic, bulgur, chicken, peas unthawed, freshly-grated Parmesan cheese, whipping cream, Parmesan cheese | task571_recipe_nlg_ner_generation | NIv2 | zs_opt | 8 | test |
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
In a small frying pan, on medium low heat, toast the cumin, cloves, cardamom, pe... | cumin seeds, cloves, cardamom seeds, black peppercorns, allspice, fenugreek seeds, coriander seeds, red chiles, ginger root, turmeric, salt, paprika, cinnamon, cloves ground | task571_recipe_nlg_ner_generation | NIv2 | zs_opt | 5 | validation |
Definition: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Input: Sentence 1: Dissenting in the New York Times Book Review , Pico Iyer finds Cu... | 4 | task198_mnli_domain_classification | NIv2 | zs_opt | 2 | train |
Q: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Sentence 1: That's all." Tuppence rose. Sentence 2: Tuppence continued on speaking. Choices: ... | 9 | task198_mnli_domain_classification | NIv2 | zs_opt | 7 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Sentence 1: And, a... | 1 | task198_mnli_domain_classification | NIv2 | zs_opt | 1 | train |
Instructions: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Input: Sentence 1: we have had no snow to speak of to speak of Sentence 2: We did ... | 5 | task198_mnli_domain_classification | NIv2 | zs_opt | 3 | train |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Example: Sentence 1: Next to the MGM Grand you will find M and M World. Sentence 2: The candy ha... | Solution: 5 | task198_mnli_domain_classification | NIv2 | fs_opt | 5 | train |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Q: Sentence 1: Employers wishing to avoid paying workers compensation could deny coverage until... | 5
****
| task198_mnli_domain_classification | NIv2 | fs_opt | 4 | train |
Instructions: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Input: Sentence 1: The Commission stated that a date stamp on a telephone would in... | 1 | task198_mnli_domain_classification | NIv2 | zs_opt | 3 | train |
Given the task definition and input, reply with output. In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Sentence 1: Buchanan pities the Lone Ea... | 4 | task198_mnli_domain_classification | NIv2 | zs_opt | 5 | train |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Example Input: Sentence 1: like i said i like it i like the heat i like the i jump out of the s... | 6
| task198_mnli_domain_classification | NIv2 | fs_opt | 3 | test |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
One example: Sentence 1: Next to the MGM Grand you will find M and M World. Sentence 2: The cand... | 6 | task198_mnli_domain_classification | NIv2 | fs_opt | 6 | validation |
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Ex Input:
System Reference: mangia tutti ristorante is a good dinner place that a... | 1
| task1186_nne_hrngo_classification | NIv2 | fs_opt | 1 | train |
Teacher:You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Teacher: Now, understand the problem? Solve this instance: System Referenc... | 1 | task1186_nne_hrngo_classification | NIv2 | zs_opt | 6 | train |
Teacher: You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Teacher: Now, understand the problem? If you are still confused, see the ... | 0 | task1186_nne_hrngo_classification | NIv2 | fs_opt | 2 | train |
Detailed Instructions: You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Q: System Reference: the name of the restaurant is angkor b... | 1 | task1186_nne_hrngo_classification | NIv2 | zs_opt | 9 | train |
You will be given a definition of a task first, then some input of the task.
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Syst... | 1 | task1186_nne_hrngo_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.
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a n... | 0 | task1186_nne_hrngo_classification | NIv2 | fs_opt | 0 | train |
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
[EX Q]: System Reference: what area are you looking for?
Original Reference: what... | 0
| task1186_nne_hrngo_classification | NIv2 | fs_opt | 6 | train |
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
System Reference: bund shanghai restaurant 's address is 640 jackson street.
Orig... | 1 | task1186_nne_hrngo_classification | NIv2 | zs_opt | 0 | train |
You will be given a definition of a task first, then some input of the task.
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Syst... | 1 | task1186_nne_hrngo_classification | NIv2 | zs_opt | 1 | test |
Teacher:You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Teacher: Now, understand the problem? Solve this instance: System Referenc... | 1 | task1186_nne_hrngo_classification | NIv2 | zs_opt | 6 | validation |
Detailed Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Problem:מה אנחנו יכולים לעשות ליתוש?
Solution: | Che possiamo fare alla zanzara? | task1111_ted_translation_he_it | NIv2 | zs_opt | 8 | train |
Detailed Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Q: זהו הישג מדהים.
A: | È un obiettivo impressionante. | task1111_ted_translation_he_it | NIv2 | zs_opt | 9 | train |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
--------
Question: וג 'יל וקווין, הזוג המאושר, חזרו מירח הדבש שלהם וגילו שהסרטון שלהם הופץ ברשת בטירוף.
Answer: E Jill e Kevin, la coppia felice, sono tornati dalla luna di miele e hanno scoperto che il loro video era divent... | Lui non avrebbe concesso la golf car, e argomentò il suo dissenso in modo interessante.
| task1111_ted_translation_he_it | NIv2 | fs_opt | 7 | train |
Q: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
האם זה סוג הפשטות שנראה ברור מאליו, או מהסוג שנראה עמוק?
A: | Questo è quel tipo di semplice che appare ovvio, o il tipo che appare profondo? | task1111_ted_translation_he_it | NIv2 | zs_opt | 7 | train |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Ex Input:
בגובה הזה, האגם חווה בדיוק אותם תנאים כמו אלו במאדים לפני 3.5 מיליארד שנים.
Ex Output:
A quest'altitudine, questo lago è sottoposto alle stesse condizioni che c'erano su Marte 3,5 miliardi di anni fa.
Ex Input:
... | Quando lavoro con Rahman che è un grande musicista, gli dico spesso, "" Non seguire ciò che già dice la sceneggiatura.
| task1111_ted_translation_he_it | NIv2 | fs_opt | 1 | train |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
[Q]: החבר 'ה האלה צריכים לשחות בתוכו.
[A]: Loro ci devono nuotare in mezzo.
[Q]: ואם נוכל להסכים גם על ערך וגם על שיטה למדוד אם הצלחנו להפחית את הפשיעה החוזרת, נוכל לעשות משהו די מעניין, לדעתנו.
[A]: E se concordiamo sia s... | Era un panorama con figure, semi vestite, che bevevano vino. C'era una donna nuda nel primo piano in basso, e una sulla collina sullo sfondo, c'era una figura del dio mitologico Bacco, e disse: "" Cos'è questo? "" Ed io — nessun altro lo fece, per cui alzai la mano e dissi: "" E 'un Baccanale di Tiziano "".
| task1111_ted_translation_he_it | NIv2 | fs_opt | 5 | train |
Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Input: יש לנו ספרים, מזנוני מזון, וגלי רדיו, כלות בחתונות, ורכבות הרים.
Output: | Abbiamo libri, buffet e onde radio, future spose e giri sulle montagne russe. | task1111_ted_translation_he_it | NIv2 | zs_opt | 3 | train |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Input: Consider Input: אני חושב שהוא צריך להיות בגזע, כי הוא איפשר את המשפחה שלי.
Output: Penso che dovrebbe stare sul tronco, perché ha reso possibile la mia famiglia.
Input: Consider Input: מישהו מרגיש מאויים, מישהו באמ... | Output: E mi sono lasciato prendere.
| task1111_ted_translation_he_it | NIv2 | fs_opt | 2 | train |
Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Input: הרעיון של אסטרטגיה בעסקים מקורה בשני ענקים אינטלקטואלים: ברוס הנדרסון, המייסד של BCG, ומייקל פורטר, פרופסור בבית הספר לעסקים של הארווארד.
Output: | L'idea di strategia nel business deve le sue origini a due giganti del pensiero: Bruce Henderson, il fondatore del Boston Consulting Group, e Michael Porter, professore alla Harvard Business School. | task1111_ted_translation_he_it | NIv2 | zs_opt | 3 | test |
Q: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
זה לא שהאנשים הדתיים יותר — אלה שזכרו יותר מהדיברות — רימו פחות, ושהאנשים הדתיים פחות — אלה שכמעט ולא הצליחו להיזכר בדיברות — רימו יותר.
A: | Non era che le persone più religiose, coloro che ricordavano meglio i 10 Comandamenti, abbiano imbrogliato meno, e i meno religiosi, quelli che quasi non ne ricordavano neanche uno, abbiano invece truffato di più. | task1111_ted_translation_he_it | NIv2 | zs_opt | 7 | validation |
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
[Q]: Tweet: I'm bored... and ready for lunch... I'm lonely... Quest... | no
| task196_sentiment140_answer_generation | NIv2 | fs_opt | 5 | train |
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Tweet: @Sampalm yes that's true omg why u wake up so early everyda... | no | task196_sentiment140_answer_generation | NIv2 | zs_opt | 0 | train |
Definition: In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Input: Tweet: Watching Sonny with a chance Question: is ... | yes | task196_sentiment140_answer_generation | NIv2 | zs_opt | 2 | train |
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Q: Tweet: Want to go home! I'm missing So You Think You Can Dance! ... | no
****
| task196_sentiment140_answer_generation | NIv2 | fs_opt | 4 | train |
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Tweet: I take no satisfaction in seeing Luongo feeling so badly. Ver... | yes | task196_sentiment140_answer_generation | NIv2 | zs_opt | 0 | train |
Teacher:In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Teacher: Now, understand the problem? Solve this instance: Tw... | yes | task196_sentiment140_answer_generation | NIv2 | zs_opt | 6 | train |
Given the task definition and input, reply with output. In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Tweet: Going... | yes | task196_sentiment140_answer_generation | NIv2 | zs_opt | 5 | train |
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Input: Consider Input: Tweet: @AnditisLiz the c-murda youtube vid go... | Output: no
| task196_sentiment140_answer_generation | NIv2 | fs_opt | 2 | train |
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Example input: Tweet: @justinchuan Awww! I was thinking about you lo... | no | task196_sentiment140_answer_generation | NIv2 | fs_opt | 3 | test |
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Example input: Tweet: @justinchuan Awww! I was thinking about you lo... | yes | task196_sentiment140_answer_generation | NIv2 | fs_opt | 3 | validation |
Choices: [I] Yes. [II] No.
Q: Do you think the right answer to the question "what do most molds get their organic compounds from?" is "particles in the air", given that molds get organic compound from dead organisms?
A: | [I] | qasc_is_correct_2 | P3 | zs_opt | 6 | train |
Do you think the right answer to the question "plants and snakes live _." is "important habitats", given that plants live just about everywhere snakes do?
OPT: (I). Yes; (II). No;
Answer: | (I). | qasc_is_correct_2 | P3 | zs_opt | 1 | train |
Do you think the right answer to the question "intelligence is primarily encoded in what?" is "rNA", given that intelligence is primarily encoded in DNA?
OPTIONS:
- Yes
- No
Answer: No
Do you think the right answer to the question "what are highly probable in the evolution of a group of bipedal dinosaurs?" is "heat... | No | qasc_is_correct_2 | P3 | fs_opt | 1 | train |
Do you think the right answer to the question "what requires investment, seed mass, size and dispersal?" is "species", given that plants require investment, seed mass, size and dispersal. ?
i. Yes.
ii. No.
Answer: | i. | qasc_is_correct_2 | P3 | zs_opt | 2 | train |
Do you think the right answer to the question "magnetism can cause objects to do what to each other?" is "kill them", given that magnetism can cause objects to push each other away?
Answer: | No | qasc_is_correct_2 | P3 | zs_noopt | 1 | train |
Problem: OPTIONS:
- Yes
- No
Q: Do you think the right answer to the question "the runaway greenhouse effect present on Venus makes what unlikely?" is "bloom time", given that venus is unlikely to be able to sustain life because of a runaway greenhouse effect?
Answer: No
Problem: OPTIONS:
- Yes
- No
Q: Do you think th... | No | qasc_is_correct_2 | P3 | fs_opt | 8 | train |
Q: Do you think the right answer to the question "what do living things require?" is "water", given that living things all require food. ? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "what redirects light in a camera?" is "microscope", given that a camera needs a mirror to help redir... | A: No | qasc_is_correct_2 | P3 | fs_opt | 2 | train |
Q: Do you think the right answer to the question "what has lower temperatures?" is "fur seals", given that the mountains have lower temperatures? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "what grows towards a light source?" is "bacteria", given that legumes grow towards a light so... | A: No | qasc_is_correct_2 | P3 | fs_opt | 2 | train |
Q: Do you think the right answer to the question "what can cause debris?" is "erosion", given that hammers cause debris?
A: | No | qasc_is_correct_2 | P3 | zs_noopt | 6 | test |
Q: Do you think the right answer to the question "vegetative life can live anywhere on earth and also share what characteristics?" is "sub-units of species", given that vegetative live just about everywhere on earth and are innovative and adaptive?
Options: (1). Yes. (2). No.
A: | (2). | qasc_is_correct_2 | P3 | zs_opt | 3 | validation |
Detailed Instructions: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the i... | not | task386_semeval_2018_task3_irony_detection | NIv2 | zs_opt | 8 | train |
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label... | not | task386_semeval_2018_task3_irony_detection | NIv2 | fs_opt | 3 | train |
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label... | ironic
| task386_semeval_2018_task3_irony_detection | NIv2 | fs_opt | 7 | train |
Detailed Instructions: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the i... | ironic | task386_semeval_2018_task3_irony_detection | NIv2 | fs_opt | 4 | train |
Instructions: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended s... | ironic | task386_semeval_2018_task3_irony_detection | NIv2 | zs_opt | 3 | train |
Teacher:In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentenc... | ironic | task386_semeval_2018_task3_irony_detection | NIv2 | zs_opt | 6 | train |
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label... | not | task386_semeval_2018_task3_irony_detection | NIv2 | fs_opt | 8 | train |
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label... | ironic
| task386_semeval_2018_task3_irony_detection | NIv2 | fs_opt | 5 | train |
Definition: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sen... | not | task386_semeval_2018_task3_irony_detection | NIv2 | zs_opt | 2 | test |
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label... | ironic
| task386_semeval_2018_task3_irony_detection | NIv2 | fs_opt | 0 | validation |
Given the task definition and input, reply with output. You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
System Reference: s... | 0 | task1284_hrngo_informativeness_classification | NIv2 | zs_opt | 5 | train |
Definition: You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Input: System Reference: what area are you looking for a hotel i... | 0 | task1284_hrngo_informativeness_classification | NIv2 | zs_opt | 2 | train |
Definition: You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Input: System Reference: the address of original us restaurant i... | 1 | task1284_hrngo_informativeness_classification | NIv2 | zs_opt | 2 | train |
Teacher:You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Teacher: Now, understand the problem? Solve this instance: System Re... | 1 | task1284_hrngo_informativeness_classification | NIv2 | zs_opt | 6 | train |
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Example: System Reference: x is a reasonably priced fast food restaurant dow... | Solution: 1 | task1284_hrngo_informativeness_classification | NIv2 | fs_opt | 5 | train |
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Example Input: System Reference: may i ask near where?
Original Reference: ... | 0
| task1284_hrngo_informativeness_classification | NIv2 | fs_opt | 3 | train |
You will be given a definition of a task first, then some input of the task.
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.... | 1 | task1284_hrngo_informativeness_classification | NIv2 | zs_opt | 1 | train |
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Q: System Reference: may i ask near where?
Original Reference: what venue d... | 1
****
| task1284_hrngo_informativeness_classification | NIv2 | fs_opt | 4 | train |
instruction:
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
question:
System Reference: x is a french restaurant in the riv... | 1
| task1284_hrngo_informativeness_classification | NIv2 | fs_opt | 9 | test |
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Example: System Reference: x is a reasonably priced fast food restaurant dow... | Solution: 0 | task1284_hrngo_informativeness_classification | NIv2 | fs_opt | 5 | validation |
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