Datasets:
Tasks:
Question Answering
Languages:
Portuguese
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
Tags:
License:
albertvillanova
HF staff
Convert dataset sizes from base 2 to base 10 in the dataset card (#2)
cdb8298
metadata
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- pt
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
- open-domain-qa
paperswithcode_id: null
pretty_name: SquadV1Pt
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
splits:
- name: train
num_bytes: 85323237
num_examples: 87599
- name: validation
num_bytes: 11265474
num_examples: 10570
download_size: 39532595
dataset_size: 96588711
Dataset Card for "squad_v1_pt"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/nunorc/squad-v1.1-pt
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 39.53 MB
- Size of the generated dataset: 96.72 MB
- Total amount of disk used: 136.25 MB
Dataset Summary
Portuguese translation of the SQuAD dataset. The translation was performed automatically using the Google Cloud API.
Supported Tasks and Leaderboards
Languages
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: astringfeature.title: astringfeature.context: astringfeature.question: astringfeature.answers: a dictionary feature containing:text: astringfeature.answer_start: aint32feature.
Data Splits
| name | train | validation |
|---|---|---|
| default | 87599 | 10570 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
@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.