Title: MLQA: Evaluating Cross-lingual Extractive Question Answering
Abstract: https://arxiv.org/abs/1910.07475
MLQA (MultiLingual Question Answering) is a benchmark dataset for evaluating cross-lingual question answering performance. MLQA consists of over 5K extractive QA instances (12K in English) in SQuAD format in seven languages - English, Arabic, German, Spanish, Hindi, Vietnamese and Simplified Chinese. MLQA is highly parallel, with QA instances parallel between 4 different languages on average
Homepage: https://github.com/facebookresearch/MLQA
@misc{lewis2020mlqaevaluatingcrosslingualextractive,
title={MLQA: Evaluating Cross-lingual Extractive Question Answering},
author={Patrick Lewis and Barlas Oğuz and Ruty Rinott and Sebastian Riedel and Holger Schwenk},
year={2020},
eprint={1910.07475},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/1910.07475},
}
- Not part of a group yet
Tasks of the form mlqa_context-lang_question-lang
mlqa_ar_armlqa_ar_demlqa_ar_vimlqa_ar_zhmlqa_ar_enmlqa_ar_esmlqa_ar_himlqa_de_armlqa_de_demlqa_de_vimlqa_de_zhmlqa_de_enmlqa_de_esmlqa_de_himlqa_vi_armlqa_vi_demlqa_vi_vimlqa_vi_zhmlqa_vi_enmlqa_vi_esmlqa_vi_himlqa_zh_armlqa_zh_demlqa_zh_vimlqa_zh_zhmlqa_zh_enmlqa_zh_esmlqa_zh_himlqa_en_armlqa_en_demlqa_en_vimlqa_en_zhmlqa_en_enmlqa_en_esmlqa_en_himlqa_es_armlqa_es_demlqa_es_vimlqa_es_zhmlqa_es_enmlqa_es_esmlqa_es_himlqa_hi_armlqa_hi_demlqa_hi_vimlqa_hi_zhmlqa_hi_enmlqa_hi_esmlqa_hi_hi
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