Datasets:

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----
-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.