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In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Let me give you an ... | bad | 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | good | 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Detailed Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good review... | bad | 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | good | 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Let me give you an ... | bad | 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[Q]: Ein Stern, wei... | bad
| 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | bad | 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Teacher: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Teacher: No... | bad | 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | bad | 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[EX Q]: Son como lo... | good
| 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
--------
Question: I... | good
| 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
One example is below... | bad | 9 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
One example: The bag... | bad | 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Input: Consider Inp... | Output: good
| 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: bad | 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
TASK DEFINITION: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
PRO... | good
| 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
TASK DEFINITION: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
PRO... | good
| 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
--------
Question: B... | bad
| 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Detailed Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good review... | good | 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Q: Ein Stern, weil ... | good
****
| 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the revi... | bad | 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Part 1. Definition
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
P... | good | 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: good | 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example input: The ... | bad | 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Ex Input:
Horrible,... | bad
| 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example input: The ... | good | 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Input: Consider Inp... | Output: bad
| 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[Q]: 半年で壊れたんで星1です て... | good
| 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example Input: Cats... | good
| 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
instruction:
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
questio... | good
| 9 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example Input: Lleg... | good
| 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Teacher: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Teacher: No... | bad | 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Input: Consider Inp... | Output: good
| 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Teacher: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Teacher: No... | good | 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: bad | 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Ex Input:
今まで有線のイヤホ... | good
| 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Detailed Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good review... | bad | 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: good | 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example Input: In d... | bad
| 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Let me give you an ... | good | 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
--------
Question: M... | good
| 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Input: Consider Inp... | Output: bad
| 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
instruction:
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
questio... | bad
| 9 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Part 1. Definition
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
P... | bad | 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | bad | 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[Q]: It's been in t... | bad
| 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
One example: The bag... | bad | 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[EX Q]: Llega tarde... | good
| 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the revi... | good | 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Detailed Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good review... | bad | 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
instruction:
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
questio... | bad
| 9 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
--------
Question: C... | good
| 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Q: Me parece muy ap... | good
****
| 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the revi... | bad | 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Part 1. Definition
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
P... | bad | 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Let me give you an ... | bad | 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
--------
Question: 値... | bad
| 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
TASK DEFINITION: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
PRO... | good
| 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Q: Si l'ampoule est... | good
****
| 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example Input: 音箱播放... | bad
| 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Detailed Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good review... | good | 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[Q]: Ein Stern, wei... | bad
| 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Ex Input:
３箇所の鍵のうち鍵... | bad
| 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[EX Q]: This produc... | bad
| 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
instruction:
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
questio... | good
| 9 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | good | 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Input: Consider Inp... | Output: good
| 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Let me give you an ... | good | 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[EX Q]: 裤子一般，穿着比较舒适... | bad
| 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Let me give you an ... | bad | 8 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
--------
Question: T... | bad
| 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Part 1. Definition
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
P... | bad | 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: bad | 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[Q]: War ganz okay.... | bad
| 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: good | 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
One example: The bag... | good | 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the revi... | good | 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
One example: The bag... | bad | 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Sehr angenehmer Duf... | bad
| 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Teacher: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Teacher: No... | bad | 2 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Part 1. Definition
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
P... | good | 7 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[EX Q]: 不好用，第一次就坏了，... | good
| 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Llega tarde y co la... | bad
| 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[Q]: Followed direc... | good
| 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the revi... | good | 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[Q]: They do what t... | good
| 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
One example: The bag... | good | 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example input: The ... | good | 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example input: The ... | good | 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example Input: Te o... | bad
| 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Ex Input:
之前给了一个三星，... | good
| 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the revi... | bad | 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example: The bags ca... | Solution: bad | 5 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Q: War ganz okay. H... | bad
****
| 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
[EX Q]: チャックの開閉時に水よ... | good
| 6 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Example input: The ... | bad | 3 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good reviews.
Ex Input:
十分な在庫を用意で... | bad
| 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Detailed Instructions: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a bad review, and positive/neutral reviews are good review... | bad | 4 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
Given the task definition, example input & output, solve the new input case.
In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the review is good or bad. A negative review is a ba... | good | 1 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review, you need to predict whether the revi... | good | 0 | NIv2 | task1575_amazon_reviews_multi_sentiment_classification | fs_opt |
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