README.md

metadata

annotations_creators:
  - machine-generated
language_creators:
  - machine-generated
language:
  - es
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - extended|squad
task_categories:
  - question-answering
task_ids:
  - extractive-qa
paperswithcode_id: squad-es
pretty_name: SQuAD-es
dataset_info:
  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
  config_name: v1.1.0
  splits:
    - name: train
      num_bytes: 83680438
      num_examples: 87595
    - name: validation
      num_bytes: 10955800
      num_examples: 10570
  download_size: 39291362
  dataset_size: 94636238

Dataset Card for "squad_es"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://github.com/ccasimiro88/TranslateAlignRetrieve
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 39.29 MB
• Size of the generated dataset: 94.63 MB
• Total amount of disk used: 133.92 MB

Dataset Summary

Automatic translation of the Stanford Question Answering Dataset (SQuAD) v2 into Spanish

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

v1.1.0

• Size of downloaded dataset files: 39.29 MB
• Size of the generated dataset: 94.63 MB
• Total amount of disk used: 133.92 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "answers": {
        "answer_start": [404, 356, 356],
        "text": ["Santa Clara, California", "Levi 's Stadium", "Levi 's Stadium en la Bahía de San Francisco en Santa Clara, California."]
    },
    "context": "\"El Super Bowl 50 fue un partido de fútbol americano para determinar al campeón de la NFL para la temporada 2015. El campeón de ...",
    "id": "56be4db0acb8001400a502ee",
    "question": "¿Dónde tuvo lugar el Super Bowl 50?",
    "title": "Super Bowl _ 50"
}

Data Fields

The data fields are the same among all splits.

v1.1.0

• 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
v1.1.0	87595	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

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

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

The SQuAD-es dataset is licensed under the CC BY 4.0 license.

Citation Information

@article{2016arXiv160605250R,
       author = {Casimiro Pio , Carrino and  Marta R. , Costa-jussa and  Jose A. R. , Fonollosa},
        title = "{Automatic Spanish Translation of the SQuAD Dataset for Multilingual
Question Answering}",
      journal = {arXiv e-prints},
         year = 2019,
          eid = {arXiv:1912.05200v1},
        pages = {arXiv:1912.05200v1},
archivePrefix = {arXiv},
       eprint = {1912.05200v2},
}

Contributions

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