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Meta4XNLI: A Crosslingual Parallel Corpus for Metaphor Detection and Interpretation

Created by
  • Haebom

Author

Elisa Sanchez-Bayona, Rodrigo Agerri

Outline

Meta4XNLI is a new parallel dataset for metaphor detection and interpretation in Spanish and English. This paper investigates the metaphor identification and understanding capabilities of language models through a series of monolingual and cross-lingual experiments using the proposed corpus. We examine the results and perform error analysis to understand the impact of figurative expressions on model performance. In addition, parallel data provides many potential opportunities to investigate the transferability of metaphors between these languages and the impact of translation on the development of multilingual annotation resources.

Takeaways, Limitations

Takeaways: The Meta4XNLI dataset provides a new resource for metaphor detection and interpretation tasks in both Spanish and English. It can help to evaluate and improve the metaphor processing ability of language models through single-language and cross-language experiments. It provides an opportunity to study the transferability of metaphors across languages and the impact of translation by leveraging parallel data.
Limitations: There is a lack of specific information about the size and composition of the Meta4XNLI dataset mentioned in the paper. A detailed description of the details and results of the error analysis is needed. A comparative analysis of the performance of various language models may be lacking.
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