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

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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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},
}

Contributions

Thanks to @thomwolf , @albertvillanova , @lewtun , @patrickvonplaten for adding this dataset.