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Dataset Card for "squad_v1_pt"

Dataset Summary

Portuguese translation of the SQuAD dataset. The translation was performed automatically using the Google Cloud API.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

Size of downloaded dataset files: 39.53 MB
Size of the generated dataset: 96.72 MB
Total amount of disk used: 136.25 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "answers": {
        "answer_start": [0],
        "text": ["Saint Bernadette Soubirous"]
    },
    "context": "\"Arquitetonicamente, a escola tem um caráter católico. No topo da cúpula de ouro do edifício principal é uma estátua de ouro da ...",
    "id": "5733be284776f41900661182",
    "question": "A quem a Virgem Maria supostamente apareceu em 1858 em Lourdes, na França?",
    "title": "University_of_Notre_Dame"
}

Data Fields

The data fields are the same among all splits.

default

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
default	87599	10570

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@article{2016arXiv160605250R,
       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
                 Konstantin and {Liang}, Percy},
        title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
      journal = {arXiv e-prints},
         year = 2016,
          eid = {arXiv:1606.05250},
        pages = {arXiv:1606.05250},
archivePrefix = {arXiv},
       eprint = {1606.05250},
}