Datasets:
Tasks:
Question Answering
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
Tags:
License:
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - crowdsourced | |
| language: | |
| - en | |
| license: | |
| - cc-by-sa-4.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 100K<n<1M | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - question-answering | |
| task_ids: | |
| - open-domain-qa | |
| - extractive-qa | |
| paperswithcode_id: squad | |
| pretty_name: SQuAD2.0 | |
| dataset_info: | |
| config_name: squad_v2 | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: title | |
| dtype: string | |
| - name: context | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: answers | |
| sequence: | |
| - name: text | |
| dtype: string | |
| - name: answer_start | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 116732025 | |
| num_examples: 130319 | |
| - name: validation | |
| num_bytes: 11661091 | |
| num_examples: 11873 | |
| download_size: 17720493 | |
| dataset_size: 128393116 | |
| configs: | |
| - config_name: squad_v2 | |
| data_files: | |
| - split: train | |
| path: squad_v2/train-* | |
| - split: validation | |
| path: squad_v2/validation-* | |
| default: true | |
| train-eval-index: | |
| - config: squad_v2 | |
| task: question-answering | |
| task_id: extractive_question_answering | |
| splits: | |
| train_split: train | |
| eval_split: validation | |
| col_mapping: | |
| question: question | |
| context: context | |
| answers: | |
| text: text | |
| answer_start: answer_start | |
| metrics: | |
| - type: squad_v2 | |
| name: SQuAD v2 | |
| # Dataset Card for SQuAD 2.0 | |
| ## Table of Contents | |
| - [Dataset Card for "squad_v2"](#dataset-card-for-squad_v2) | |
| - [Table of Contents](#table-of-contents) | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [squad_v2](#squad_v2) | |
| - [Data Fields](#data-fields) | |
| - [squad_v2](#squad_v2-1) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) | |
| - [Who are the source language producers?](#who-are-the-source-language-producers) | |
| - [Annotations](#annotations) | |
| - [Annotation process](#annotation-process) | |
| - [Who are the annotators?](#who-are-the-annotators) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** https://rajpurkar.github.io/SQuAD-explorer/ | |
| - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| - **Paper:** https://arxiv.org/abs/1806.03822 | |
| - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Dataset Summary | |
| 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. | |
| SQuAD 2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers | |
| to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but | |
| also determine when no answer is supported by the paragraph and abstain from answering. | |
| ### Supported Tasks and Leaderboards | |
| Question Answering. | |
| ### Languages | |
| English (`en`). | |
| ## Dataset Structure | |
| ### Data Instances | |
| #### squad_v2 | |
| - **Size of downloaded dataset files:** 46.49 MB | |
| - **Size of the generated dataset:** 128.52 MB | |
| - **Total amount of disk used:** 175.02 MB | |
| An example of 'validation' looks as follows. | |
| ``` | |
| This example was too long and was cropped: | |
| { | |
| "answers": { | |
| "answer_start": [94, 87, 94, 94], | |
| "text": ["10th and 11th centuries", "in the 10th and 11th centuries", "10th and 11th centuries", "10th and 11th centuries"] | |
| }, | |
| "context": "\"The Normans (Norman: Nourmands; French: Normands; Latin: Normanni) were the people who in the 10th and 11th centuries gave thei...", | |
| "id": "56ddde6b9a695914005b9629", | |
| "question": "When were the Normans in Normandy?", | |
| "title": "Normans" | |
| } | |
| ``` | |
| ### Data Fields | |
| The data fields are the same among all splits. | |
| #### squad_v2 | |
| - `id`: a `string` feature. | |
| - `title`: a `string` feature. | |
| - `context`: a `string` feature. | |
| - `question`: a `string` feature. | |
| - `answers`: a dictionary feature containing: | |
| - `text`: a `string` feature. | |
| - `answer_start`: a `int32` feature. | |
| ### Data Splits | |
| | name | train | validation | | |
| | -------- | -----: | ---------: | | |
| | squad_v2 | 130319 | 11873 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the source language producers? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| #### Who are the annotators? | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Personal and Sensitive Information | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Discussion of Biases | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Other Known Limitations | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
| ### Licensing Information | |
| The dataset is distributed under the CC BY-SA 4.0 license. | |
| ### Citation Information | |
| ``` | |
| @inproceedings{rajpurkar-etal-2018-know, | |
| title = "Know What You Don{'}t Know: Unanswerable Questions for {SQ}u{AD}", | |
| author = "Rajpurkar, Pranav and | |
| Jia, Robin and | |
| Liang, Percy", | |
| editor = "Gurevych, Iryna and | |
| Miyao, Yusuke", | |
| booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)", | |
| month = jul, | |
| year = "2018", | |
| address = "Melbourne, Australia", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/P18-2124", | |
| doi = "10.18653/v1/P18-2124", | |
| pages = "784--789", | |
| eprint={1806.03822}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| @inproceedings{rajpurkar-etal-2016-squad, | |
| title = "{SQ}u{AD}: 100,000+ Questions for Machine Comprehension of Text", | |
| author = "Rajpurkar, Pranav and | |
| Zhang, Jian and | |
| Lopyrev, Konstantin and | |
| Liang, Percy", | |
| editor = "Su, Jian and | |
| Duh, Kevin and | |
| Carreras, Xavier", | |
| booktitle = "Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing", | |
| month = nov, | |
| year = "2016", | |
| address = "Austin, Texas", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/D16-1264", | |
| doi = "10.18653/v1/D16-1264", | |
| pages = "2383--2392", | |
| eprint={1606.05250}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@lewtun](https://github.com/lewtun), [@albertvillanova](https://github.com/albertvillanova), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset. |