metadata

annotations_creators:
  - crowdsourced
language_creators:
  - crowdsourced
  - found
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - extended|wikipedia
task_categories:
  - question-answering
task_ids:
  - extractive-qa
paperswithcode_id: squad
pretty_name: SQuAD

Dataset Card for "squad"

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://rajpurkar.github.io/SQuAD-explorer/
Repository: More Information Needed
Paper: More Information Needed
Point of Contact: More Information Needed
Size of downloaded dataset files: 33.51 MB
Size of the generated dataset: 85.75 MB
Total amount of disk used: 119.27 MB

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.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

plain_text

Size of downloaded dataset files: 33.51 MB
Size of the generated dataset: 85.75 MB
Total amount of disk used: 119.27 MB

An example of 'train' looks as follows.

{
    "answers": {
        "answer_start": [1],
        "text": ["This is a test text"]
    },
    "context": "This is a test context.",
    "id": 1,
    "question": "Is this a test?",
}

Data Fields

The data fields are the same among all splits.

plain_text

id: a int32 feature.
context: a string feature.
question: a string feature.
answers: a dictionary feature containing:
- text: a string feature.
- answer_start: a int32 feature.