Title: XNLIeu: a dataset for cross-lingual NLI in Basque
Abstract: https://arxiv.org/abs/2404.06996
XNLI is a popular Natural Language Inference (NLI) benchmark widely used to evaluate cross-lingual Natural Language Understanding (NLU) capabilities across languages. In this paper, we expand XNLI to include Basque, a low-resource language that can greatly benefit from transfer-learning approaches. The new dataset, dubbed XNLIeu, has been developed by first machine-translating the English XNLI corpus into Basque, followed by a manual post-edition step. We have conducted a series of experiments using mono- and multilingual LLMs to assess a) the effect of professional post-edition on the MT system; b) the best cross-lingual strategy for NLI in Basque; and c) whether the choice of the best cross-lingual strategy is influenced by the fact that the dataset is built by translation. The results show that post-edition is necessary and that the translate-train cross-lingual strategy obtains better results overall, although the gain is lower when tested in a dataset that has been built natively from scratch. Our code and datasets are publicly available under open licenses at https://github.com/hitz-zentroa/xnli-eu.
Homepage: https://github.com/hitz-zentroa/xnli-eu
@misc{heredia2024xnlieu,
title={XNLIeu: a dataset for cross-lingual NLI in Basque},
author={Maite Heredia and Julen Etxaniz and Muitze Zulaika and Xabier Saralegi and Jeremy Barnes and Aitor Soroa},
year={2024},
eprint={2404.06996},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
xnli_eu_mt_native
: Includes MT and Native variants of the XNLIeu dataset.
xnli_eu
: XNLI in Basque postedited from MT.xnli_eu_mt
: XNLI in Basque machine translated from English.xnli_eu_native
: XNLI in Basque natively created.
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