YAML tags: null
annotations_creators:
- found
language_creators:
- found
- expert-generated
languages:
- hu
licenses:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: HuRC
size_categories:
- unknown
source_datasets:
- extended|other
task_categories:
- question-answering
task_ids:
- extractive-qa
- abstractive-qa
Dataset Card for HuRC
Table of Contents
Dataset Description
- Homepage:
- Repository: HuRC dataset
- Paper:
- Leaderboard:
- Point of Contact: lnnoemi
Dataset Summary
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Languages
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Dataset Structure
Data Instances
For each instance, there is an id, a sentence, a question and two possible answers, and a correct answer.
An example:
{
}
Data Fields
Data Splits
Dataset Creation
Source Data
Initial Data Collection and Normalization
The data is a translation of the English Winograd schemas. Each schema was translated by a human translator. Each translation was manually checked and further refined by another annotator. Each schema was manually curated by a linguistic expert.
Additional Information
Licensing Information
HuRC is released under the BSD 2-Clause License.
Citation Information
If you use this resource or any part of its documentation, please refer to:
Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Vadász, T. (2022) HuLU: magyar nyelvű benchmark adatbázis
kiépítése a neurális nyelvmodellek kiértékelése céljából [HuLU: Hungarian benchmark dataset to evaluate neural language models]. XVIII. Magyar Számítógépes Nyelvészeti Konferencia. (in press)
@inproceedings{ligetinagy2022hulu,
title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából},
author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Vadász, T.},
booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia},
year={2022}
}
Contributions
Thanks to lnnoemi for adding this dataset.