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Update dataset card (#8)

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- Update dataset card (d7df8e6afcfb0896687d1f6093694eeb7f7d9263)

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  1. README.md +50 -23
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@@ -72,7 +72,7 @@ train-eval-index:
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  name: SQuAD v2
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  ---
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- # Dataset Card for "squad_v2"
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  ## Table of Contents
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  - [Dataset Card for "squad_v2"](#dataset-card-for-squad_v2)
@@ -108,27 +108,26 @@ train-eval-index:
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  ## Dataset Description
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- - **Homepage:** [https://rajpurkar.github.io/SQuAD-explorer/](https://rajpurkar.github.io/SQuAD-explorer/)
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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:** 46.49 MB
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- - **Size of the generated dataset:** 128.52 MB
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- - **Total amount of disk used:** 175.02 MB
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  ### Dataset Summary
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- combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers
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- to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but
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- also determine when no answer is supported by the paragraph and abstain from answering.
 
 
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  ### Supported Tasks and Leaderboards
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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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- [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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  ## Dataset Structure
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@@ -227,23 +226,51 @@ 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{2016arXiv160605250R,
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- author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
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- Konstantin and {Liang}, Percy},
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- title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
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- journal = {arXiv e-prints},
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- year = 2016,
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- eid = {arXiv:1606.05250},
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- pages = {arXiv:1606.05250},
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- archivePrefix = {arXiv},
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- eprint = {1606.05250},
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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-
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  ```
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  name: SQuAD v2
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  ---
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+ # Dataset Card for SQuAD 2.0
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  ## Table of Contents
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  - [Dataset Card for "squad_v2"](#dataset-card-for-squad_v2)
 
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  ## Dataset Description
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+ - **Homepage:** https://rajpurkar.github.io/SQuAD-explorer/
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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:** https://arxiv.org/abs/1806.03822
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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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  ### Dataset Summary
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+ Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
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+
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+ SQuAD 2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers
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+ to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but
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+ also determine when no answer is supported by the paragraph and abstain from answering.
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  ### Supported Tasks and Leaderboards
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+ Question Answering.
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  ### Languages
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+ English (`en`).
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  ## Dataset Structure
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  ### Licensing Information
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+ The dataset is distributed under the CC BY-SA 4.0 license.
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  ### Citation Information
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  ```
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+ @inproceedings{rajpurkar-etal-2018-know,
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+ title = "Know What You Don{'}t Know: Unanswerable Questions for {SQ}u{AD}",
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+ author = "Rajpurkar, Pranav and
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+ Jia, Robin and
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+ Liang, Percy",
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+ editor = "Gurevych, Iryna and
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+ Miyao, Yusuke",
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+ booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
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+ month = jul,
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+ year = "2018",
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+ address = "Melbourne, Australia",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/P18-2124",
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+ doi = "10.18653/v1/P18-2124",
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+ pages = "784--789",
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+ eprint={1806.03822},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+ @inproceedings{rajpurkar-etal-2016-squad,
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+ title = "{SQ}u{AD}: 100,000+ Questions for Machine Comprehension of Text",
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+ author = "Rajpurkar, Pranav and
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+ Zhang, Jian and
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+ Lopyrev, Konstantin and
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+ Liang, Percy",
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+ editor = "Su, Jian and
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+ Duh, Kevin and
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+ Carreras, Xavier",
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+ booktitle = "Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing",
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+ month = nov,
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+ year = "2016",
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+ address = "Austin, Texas",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/D16-1264",
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+ doi = "10.18653/v1/D16-1264",
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+ pages = "2383--2392",
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+ eprint={1606.05250},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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  }
 
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  ```
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