The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets
library). If this is not possible, please
open a discussion
for direct help.
Dataset Card for FQuAD
Dataset Summary
FQuAD: French Question Answering Dataset We introduce FQuAD, a native French Question Answering Dataset.
FQuAD contains 25,000+ question and answer pairs. Finetuning CamemBERT on FQuAD yields a F1 score of 88% and an exact match of 77.9%. Developped to provide a SQuAD equivalent in the French language. Questions are original and based on high quality Wikipedia articles.
Please, note this dataset is licensed for non-commercial purposes and users must agree to the following terms and conditions:
- Use FQuAD only for internal research purposes.
- Not make any copy except a safety one.
- Not redistribute it (or part of it) in any way, even for free.
- Not sell it or use it for any commercial purpose. Contact us for a possible commercial licence.
- Mention the corpus origin and Illuin Technology in all publications about experiments using FQuAD.
- Redistribute to Illuin Technology any improved or enriched version you could make of that corpus.
Request manually download of the data from: https://fquad.illuin.tech/
Supported Tasks and Leaderboards
closed-domain-qa
,text-retrieval
: This dataset is intended to be used forclosed-domain-qa
, but can also be used for information retrieval tasks.
Languages
This dataset is exclusively in French, with context data from Wikipedia and questions from French university students (fr
).
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 3.29 MB
- Size of the generated dataset: 6.94 MB
- Total amount of disk used: 10.23 MB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"answers": {
"answers_starts": [161, 46, 204],
"texts": ["La Vierge aux rochers", "documents contemporains", "objets de spéculations"]
},
"context": "\"Les deux tableaux sont certes décrits par des documents contemporains à leur création mais ceux-ci ne le font qu'indirectement ...",
"questions": ["Que concerne principalement les documents ?", "Par quoi sont décrit les deux tableaux ?", "Quels types d'objets sont les deux tableaux aux yeux des chercheurs ?"]
}
Data Fields
The data fields are the same among all splits.
default
context
: astring
feature.questions
: alist
ofstring
features.answers
: a dictionary feature containing:texts
: astring
feature.answers_starts
: aint32
feature.
Data Splits
The FQuAD dataset has 3 splits: train, validation, and test. The test split is however not released publicly at the moment. The splits contain disjoint sets of articles. The following table contains stats about each split.
Dataset Split | Number of Articles in Split | Number of paragraphs in split | Number of questions in split |
---|---|---|---|
Train | 117 | 4921 | 20731 |
Validation | 768 | 51.0% | 3188 |
Test | 10 | 532 | 2189 |
Dataset Creation
Curation Rationale
The FQuAD dataset was created by Illuin technology. It was developped to provide a SQuAD equivalent in the French language. Questions are original and based on high quality Wikipedia articles.
Source Data
The text used for the contexts are from the curated list of French High-Quality Wikipedia articles.
Annotations
Annotations (spans and questions) are written by students of the CentraleSupélec school of engineering. Wikipedia articles were scraped and Illuin used an internally-developped tool to help annotators ask questions and indicate the answer spans. Annotators were given paragraph sized contexts and asked to generate 4/5 non-trivial questions about information in the context.
Personal and Sensitive Information
No personal or sensitive information is included in this dataset. This has been manually verified by the dataset curators.
Considerations for Using the Data
Users should consider this dataset is sampled from Wikipedia data which might not be representative of all QA use cases.
Social Impact of Dataset
The social biases of this dataset have not yet been investigated.
Discussion of Biases
The social biases of this dataset have not yet been investigated, though articles have been selected by their quality and objectivity.
Other Known Limitations
The limitations of the FQuAD dataset have not yet been investigated.
Additional Information
Dataset Curators
Illuin Technology: https://fquad.illuin.tech/
Licensing Information
The FQuAD dataset is licensed under the CC BY-NC-SA 3.0 license.
It allows personal and academic research uses of the dataset, but not commercial uses. So concretely, the dataset cannot be used to train a model that is then put into production within a business or a company. For this type of commercial use, we invite FQuAD users to contact the authors to discuss possible partnerships.
Citation Information
@ARTICLE{2020arXiv200206071
author = {Martin, d'Hoffschmidt and Maxime, Vidal and
Wacim, Belblidia and Tom, Brendlé},
title = "{FQuAD: French Question Answering Dataset}",
journal = {arXiv e-prints},
keywords = {Computer Science - Computation and Language},
year = "2020",
month = "Feb",
eid = {arXiv:2002.06071},
pages = {arXiv:2002.06071},
archivePrefix = {arXiv},
eprint = {2002.06071},
primaryClass = {cs.CL}
}
Contributions
Thanks to @thomwolf, @mariamabarham, @patrickvonplaten, @lewtun, @albertvillanova for adding this dataset. Thanks to @ManuelFay for providing information on the dataset creation process.
- Downloads last month
- 187