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XNLIeu

Paper

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

Citation

@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}
}

Groups and Tasks

Groups

  • xnli_eu_mt_native: Includes MT and Native variants of the XNLIeu dataset.

Tasks

  • 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.

Checklist

For adding novel benchmarks/datasets to the library:

  • Is the task an existing benchmark in the literature?
    • Have you referenced the original paper that introduced the task?
    • If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?

If other tasks on this dataset are already supported:

  • Is the "Main" variant of this task clearly denoted?
  • Have you provided a short sentence in a README on what each new variant adds / evaluates?
  • Have you noted which, if any, published evaluation setups are matched by this variant?