Title: XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
Abstract: https://ducdauge.github.io/files/xcopa.pdf
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around the globe. The dataset is challenging as it requires both the command of world knowledge and the ability to generalise to new languages. All the details about the creation of XCOPA and the implementation of the baselines are available in the paper.
Homepage: https://github.com/cambridgeltl/xcopa
@inproceedings{ponti2020xcopa,
title={{XCOPA: A} Multilingual Dataset for Causal Commonsense Reasoning},
author={Edoardo M. Ponti, Goran Glava\v{s}, Olga Majewska, Qianchu Liu, Ivan Vuli\'{c} and Anna Korhonen},
booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
year={2020},
url={https://ducdauge.github.io/files/xcopa.pdf}
}
xcopa
xcopa_et
: Estonianxcopa_ht
: Haitian Creolexcopa_id
: Indonesianxcopa_it
: Italianxcopa_qu
: Cusco-Collao Quechuaxcopa_sw
: Kiswahilixcopa_ta
: Tamilxcopa_th
: Thaixcopa_tr
: Turkishxcopa_vi
: Vietnamesexcopa_zh
: Mandarin Chinese
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