Datasets:
Tasks:
Question Answering
Modalities:
Text
Sub-tasks:
open-domain-qa
Languages:
Indonesian
Size:
10K - 100K
License:
original copy from `commonsense_qa`
Browse files- README.md +222 -1
- commonsense_qa.py +102 -0
- dataset_infos.json +1 -0
- gitattributes.txt +27 -0
README.md
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---
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1 |
---
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+
annotations_creators:
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- crowdsourced
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language_creators:
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- crowdsourced
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language:
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- en
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license:
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- mit
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multilinguality:
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- monolingual
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pretty_name: CommonsenseQA
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size_categories:
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- 1K<n<10K
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source_datasets:
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- original
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task_categories:
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- question-answering
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task_ids:
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- open-domain-qa
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paperswithcode_id: commonsenseqa
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dataset_info:
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features:
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- name: id
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dtype: string
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- name: question
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dtype: string
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- name: question_concept
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dtype: string
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- name: choices
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sequence:
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- name: label
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dtype: string
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- name: text
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dtype: string
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- name: answerKey
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dtype: string
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splits:
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- name: train
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num_bytes: 2209044
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num_examples: 9741
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- name: validation
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num_bytes: 274033
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num_examples: 1221
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- name: test
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num_bytes: 258017
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num_examples: 1140
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download_size: 4680691
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dataset_size: 2741094
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---
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+
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# Dataset Card for "commonsense_qa"
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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+
- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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+
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- **Homepage:** https://www.tau-nlp.org/commonsenseqa
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- **Repository:** https://github.com/jonathanherzig/commonsenseqa
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- **Paper:** https://arxiv.org/abs/1811.00937
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- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Size of downloaded dataset files:** 4.68 MB
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- **Size of the generated dataset:** 2.18 MB
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- **Total amount of disk used:** 6.86 MB
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### Dataset Summary
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+
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CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge
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to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers.
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+
The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation
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split, and "Question token split", see paper for details.
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+
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### Supported Tasks and Leaderboards
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+
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Languages
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The dataset is in English (`en`).
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## Dataset Structure
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### Data Instances
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#### default
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- **Size of downloaded dataset files:** 4.68 MB
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- **Size of the generated dataset:** 2.18 MB
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- **Total amount of disk used:** 6.86 MB
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An example of 'train' looks as follows:
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```
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{'id': '075e483d21c29a511267ef62bedc0461',
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'question': 'The sanctions against the school were a punishing blow, and they seemed to what the efforts the school had made to change?',
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'question_concept': 'punishing',
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'choices': {'label': ['A', 'B', 'C', 'D', 'E'],
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'text': ['ignore', 'enforce', 'authoritarian', 'yell at', 'avoid']},
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'answerKey': 'A'}
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```
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### Data Fields
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The data fields are the same among all splits.
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#### default
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- `id` (`str`): Unique ID.
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- `question`: a `string` feature.
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- `question_concept` (`str`): ConceptNet concept associated to the question.
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- `choices`: a dictionary feature containing:
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- `label`: a `string` feature.
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- `text`: a `string` feature.
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- `answerKey`: a `string` feature.
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### Data Splits
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| name | train | validation | test |
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|---------|------:|-----------:|-----:|
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| default | 9741 | 1221 | 1140 |
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## Dataset Creation
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### Curation Rationale
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+
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+
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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#### Who are the source language producers?
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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### Annotations
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#### Annotation process
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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#### Who are the annotators?
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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### Personal and Sensitive Information
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+
|
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+
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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## Considerations for Using the Data
|
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+
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+
### Social Impact of Dataset
|
176 |
+
|
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+
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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+
|
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+
### Discussion of Biases
|
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+
|
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+
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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+
|
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+
### Other Known Limitations
|
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+
|
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+
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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## Additional Information
|
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+
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### Dataset Curators
|
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+
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Licensing Information
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The dataset is licensed under the MIT License.
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See: https://github.com/jonathanherzig/commonsenseqa/issues/5
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### Citation Information
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```
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@inproceedings{talmor-etal-2019-commonsenseqa,
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title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge",
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author = "Talmor, Alon and
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Herzig, Jonathan and
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Lourie, Nicholas and
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Berant, Jonathan",
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booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
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month = jun,
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year = "2019",
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address = "Minneapolis, Minnesota",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/N19-1421",
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doi = "10.18653/v1/N19-1421",
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pages = "4149--4158",
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archivePrefix = "arXiv",
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eprint = "1811.00937",
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primaryClass = "cs",
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}
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```
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### Contributions
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Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@albertvillanova](https://github.com/albertvillanova), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.
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commonsense_qa.py
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"""CommonsenseQA dataset."""
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import json
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import datasets
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_HOMEPAGE = "https://www.tau-nlp.org/commonsenseqa"
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_DESCRIPTION = """\
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CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge
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13 |
+
to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers.
|
14 |
+
The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation
|
15 |
+
split, and "Question token split", see paper for details.
|
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+
"""
|
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+
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_CITATION = """\
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@inproceedings{talmor-etal-2019-commonsenseqa,
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title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge",
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+
author = "Talmor, Alon and
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+
Herzig, Jonathan and
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+
Lourie, Nicholas and
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+
Berant, Jonathan",
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booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
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+
month = jun,
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27 |
+
year = "2019",
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+
address = "Minneapolis, Minnesota",
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29 |
+
publisher = "Association for Computational Linguistics",
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+
url = "https://aclanthology.org/N19-1421",
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+
doi = "10.18653/v1/N19-1421",
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+
pages = "4149--4158",
|
33 |
+
archivePrefix = "arXiv",
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34 |
+
eprint = "1811.00937",
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+
primaryClass = "cs",
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}
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"""
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_URL = "https://s3.amazonaws.com/commensenseqa"
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_URLS = {
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"train": f"{_URL}/train_rand_split.jsonl",
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"validation": f"{_URL}/dev_rand_split.jsonl",
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"test": f"{_URL}/test_rand_split_no_answers.jsonl",
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}
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class CommonsenseQa(datasets.GeneratorBasedBuilder):
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"""CommonsenseQA dataset."""
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VERSION = datasets.Version("1.0.0")
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def _info(self):
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features = datasets.Features(
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{
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"id": datasets.Value("string"),
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"question": datasets.Value("string"),
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"question_concept": datasets.Value("string"),
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"choices": datasets.features.Sequence(
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{
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"label": datasets.Value("string"),
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"text": datasets.Value("string"),
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}
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),
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"answerKey": datasets.Value("string"),
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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+
features=features,
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+
homepage=_HOMEPAGE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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filepaths = dl_manager.download_and_extract(_URLS)
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77 |
+
splits = [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]
|
78 |
+
return [
|
79 |
+
datasets.SplitGenerator(
|
80 |
+
name=split,
|
81 |
+
gen_kwargs={
|
82 |
+
"filepath": filepaths[split],
|
83 |
+
},
|
84 |
+
)
|
85 |
+
for split in splits
|
86 |
+
]
|
87 |
+
|
88 |
+
def _generate_examples(self, filepath):
|
89 |
+
"""Yields examples."""
|
90 |
+
with open(filepath, encoding="utf-8") as f:
|
91 |
+
for uid, row in enumerate(f):
|
92 |
+
data = json.loads(row)
|
93 |
+
choices = data["question"]["choices"]
|
94 |
+
labels = [label["label"] for label in choices]
|
95 |
+
texts = [text["text"] for text in choices]
|
96 |
+
yield uid, {
|
97 |
+
"id": data["id"],
|
98 |
+
"question": data["question"]["stem"],
|
99 |
+
"question_concept": data["question"]["question_concept"],
|
100 |
+
"choices": {"label": labels, "text": texts},
|
101 |
+
"answerKey": data.get("answerKey", ""),
|
102 |
+
}
|
dataset_infos.json
ADDED
@@ -0,0 +1 @@
|
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|
1 |
+
{"default": {"description": "CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge\nto predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers.\nThe dataset is provided in two major training/validation/testing set splits: \"Random split\" which is the main evaluation\nsplit, and \"Question token split\", see paper for details.\n", "citation": "@inproceedings{talmor-etal-2019-commonsenseqa,\n title = \"{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge\",\n author = \"Talmor, Alon and\n Herzig, Jonathan and\n Lourie, Nicholas and\n Berant, Jonathan\",\n booktitle = \"Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)\",\n month = jun,\n year = \"2019\",\n address = \"Minneapolis, Minnesota\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://aclanthology.org/N19-1421\",\n doi = \"10.18653/v1/N19-1421\",\n pages = \"4149--4158\",\n archivePrefix = \"arXiv\",\n eprint = \"1811.00937\",\n primaryClass = \"cs\",\n}\n", "homepage": "https://www.tau-nlp.org/commonsenseqa", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "question_concept": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"label": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "commonsense_qa", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2209044, "num_examples": 9741, "dataset_name": "commonsense_qa"}, "validation": {"name": "validation", "num_bytes": 274033, "num_examples": 1221, "dataset_name": "commonsense_qa"}, "test": {"name": "test", "num_bytes": 258017, "num_examples": 1140, "dataset_name": "commonsense_qa"}}, "download_checksums": {"https://s3.amazonaws.com/commensenseqa/train_rand_split.jsonl": {"num_bytes": 3785890, "checksum": "58ffa3c8472410e24b8c43f423d89c8a003d8284698a6ed7874355dedd09a2fb"}, "https://s3.amazonaws.com/commensenseqa/dev_rand_split.jsonl": {"num_bytes": 471653, "checksum": "3210497fdaae614ac085d9eb873dd7f4d49b6f965a93adadc803e1229fd8a02a"}, "https://s3.amazonaws.com/commensenseqa/test_rand_split_no_answers.jsonl": {"num_bytes": 423148, "checksum": "b426896d71a9cd064cf01cfaf6e920817c51701ef66028883ac1af2e73ad5f29"}}, "download_size": 4680691, "post_processing_size": null, "dataset_size": 2741094, "size_in_bytes": 7421785}}
|
gitattributes.txt
ADDED
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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+
*.bin filter=lfs diff=lfs merge=lfs -text
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*.bin.* filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.gz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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+
*.joblib filter=lfs diff=lfs merge=lfs -text
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+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
|
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+
*.msgpack filter=lfs diff=lfs merge=lfs -text
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+
*.onnx filter=lfs diff=lfs merge=lfs -text
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+
*.ot filter=lfs diff=lfs merge=lfs -text
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+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
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+
*.pb filter=lfs diff=lfs merge=lfs -text
|
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+
*.pt filter=lfs diff=lfs merge=lfs -text
|
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+
*.pth filter=lfs diff=lfs merge=lfs -text
|
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+
*.rar filter=lfs diff=lfs merge=lfs -text
|
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+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
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+
*.tflite filter=lfs diff=lfs merge=lfs -text
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+
*.tgz filter=lfs diff=lfs merge=lfs -text
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+
*.xz filter=lfs diff=lfs merge=lfs -text
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+
*.zip filter=lfs diff=lfs merge=lfs -text
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+
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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