task_categories:question-answering size_categories:1M<n<10M language:en license:mit sports open-domain-qa extractive-qa region:us
---
license: mit
task_categories:
- question-answering
language:
- en
tags:
- sports
- open-domain-qa
- extractive-qa
size_categories:
- 1M<n<10M
---

### Dataset Summary

QASports is the first large sports-themed question answering dataset, using as documents the wiki of 3 of the most popular sports in the world, Soccer, Football and Basketball.

Each sport can be downloaded individually as a subset, with the train, test and validation splits, or all 3 can be downloaded together.


### Supported Tasks and Leaderboards

Extractive Question Answering.

### Languages

English.

## Dataset Structure

### Data Instances

An example of 'train' looks as follows.
```
{
    "answer": {
        "offset": [42,44],
        "text": "16"
    },
    "context": "The following is a list of squads for all 16 national teams competing at the Copa América Centenario. Each national team had to submit a squad of 23 players, 3 of whom must be goalkeepers. The provisional squads were announced on 4 May 2016. A final selection was provided to the organisers on 20 May 2016."	,
    "qa_id": "61200579912616854316543272456523433217",
    "question": "How many national teams competed at the Copa América Centenario?",
    "context_id": "171084087809998484545703642399578583178",
    "context_title": "Copa América Centenario squads | Football Wiki | Fandom",
    "url": "https://football.fandom.com/wiki/Copa_Am%C3%A9rica_Centenario_squads"	

}
```
### Data Fields

The data fields are the same among all splits.

- `id_qa`: a `string` feature.
- `context_id`: a `string` feature.
- `context_title`: a `string` feature.
- `url`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `offset`: a list feature containing:
    - 2 `int32` features for start and end.