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albertvillanova HF staff commited on
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Fix missing tags in dataset cards (#4921)

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* Fix missing tags in dataset cards

* Force CI re-run

Commit from https://github.com/huggingface/datasets/commit/a0b6402e8f32a806b1ef0ff4b99fd58e54232d49

Files changed (1) hide show
  1. README.md +45 -12
README.md CHANGED
@@ -1,7 +1,23 @@
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  ---
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- pretty_name: RACE
 
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  language:
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  - en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  paperswithcode_id: race
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  ---
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@@ -34,16 +50,16 @@ paperswithcode_id: race
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  ## Dataset Description
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  - **Homepage:** [http://www.cs.cmu.edu/~glai1/data/race/](http://www.cs.cmu.edu/~glai1/data/race/)
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- - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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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:** 72.79 MB
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  - **Size of the generated dataset:** 333.27 MB
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  - **Total amount of disk used:** 406.07 MB
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  ### Dataset Summary
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- Race is a large-scale reading comprehension dataset with more than 28,000 passages and nearly 100,000 questions. The
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  dataset is collected from English examinations in China, which are designed for middle school and high school students.
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  The dataset can be served as the training and test sets for machine comprehension.
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@@ -201,18 +217,35 @@ The data fields are the same among all splits.
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  ### Licensing Information
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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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  ### Citation Information
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  ```
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- @article{lai2017large,
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- title={RACE: Large-scale ReAding Comprehension Dataset From Examinations},
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- author={Lai, Guokun and Xie, Qizhe and Liu, Hanxiao and Yang, Yiming and Hovy, Eduard},
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- journal={arXiv preprint arXiv:1704.04683},
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- year={2017}
 
 
 
 
 
 
 
 
 
 
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  }
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-
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  ```
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  ---
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+ annotations_creators:
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+ - expert-generated
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  language:
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  - en
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+ language_creators:
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+ - found
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+ license:
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+ - other
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+ multilinguality:
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+ - monolingual
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+ pretty_name: RACE
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+ size_categories:
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+ - 10K<n<100K
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - multiple-choice
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+ task_ids:
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+ - multiple-choice-qa
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  paperswithcode_id: race
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  ---
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  ## Dataset Description
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  - **Homepage:** [http://www.cs.cmu.edu/~glai1/data/race/](http://www.cs.cmu.edu/~glai1/data/race/)
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+ - **Repository:** https://github.com/qizhex/RACE_AR_baselines
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+ - **Paper:** [RACE: Large-scale ReAding Comprehension Dataset From Examinations](https://arxiv.org/abs/1704.04683)
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+ - **Point of Contact:** [Guokun Lai](mailto:[email protected]), [Qizhe Xie](mailto:qzxie@cs.cmu.edu)
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  - **Size of downloaded dataset files:** 72.79 MB
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  - **Size of the generated dataset:** 333.27 MB
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  - **Total amount of disk used:** 406.07 MB
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  ### Dataset Summary
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+ RACE is a large-scale reading comprehension dataset with more than 28,000 passages and nearly 100,000 questions. The
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  dataset is collected from English examinations in China, which are designed for middle school and high school students.
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  The dataset can be served as the training and test sets for machine comprehension.
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  ### Licensing Information
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+ http://www.cs.cmu.edu/~glai1/data/race/
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+
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+ 1. RACE dataset is available for non-commercial research purpose only.
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+
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+ 2. All passages are obtained from the Internet which is not property of Carnegie Mellon University. We are not responsible for the content nor the meaning of these passages.
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+
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+ 3. You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purpose, any portion of the contexts and any portion of derived data.
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+
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+ 4. We reserve the right to terminate your access to the RACE dataset at any time.
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  ### Citation Information
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  ```
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+ @inproceedings{lai-etal-2017-race,
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+ title = "{RACE}: Large-scale {R}e{A}ding Comprehension Dataset From Examinations",
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+ author = "Lai, Guokun and
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+ Xie, Qizhe and
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+ Liu, Hanxiao and
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+ Yang, Yiming and
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+ Hovy, Eduard",
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+ booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
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+ month = sep,
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+ year = "2017",
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+ address = "Copenhagen, Denmark",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/D17-1082",
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+ doi = "10.18653/v1/D17-1082",
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+ pages = "785--794",
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  }
 
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  ```
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