GENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena
Vanmassenhove,Eva Monti,Johanna
Vanmassenhove,Eva
Monti,Johanna
Abstract
Languages differ in terms of the absence or presence of gender features, the number of gender classes and whether and where gender features are explicitly marked. These cross-linguistic differences can lead to ambiguities that are difficult to resolve, especially for sentence-level MT systems. The identification of ambiguity and its subsequent resolution is a challenging task for which currently there aren't any specific resources or challenge sets available. In this paper, we introduce gENder- IT, an English-Italian challenge set focusing on the resolution of natural gender phenomena by providing word-level gender tags on the English source side and multiple gender alternative translations, where needed, on the Italian target side.
Description
Publisher Copyright: ©2021 Association for Computational Linguistics.
Date
2021
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Publisher
Association for Computational Linguistics (ACL)
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Keywords
Languages, Cross-linguistic Differences, Gender
Citation
Vanmassenhove, E & Monti, J 2021, GENder-IT : An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena. in M R Costa-jussa, H Gonen, C Hardmeier, C Hardmeier & K Webster (eds), GeBNLP 2021 : 3rd Workshop on Gender Bias in Natural Language Processing. vol. 3, GeBNLP 2021 - 3rd Workshop on Gender Bias in Natural Language Processing, Proceedings, Association for Computational Linguistics (ACL), online, pp. 1-7, 3rd Workshop on Gender Bias in Natural Language Processing, GeBNLP 2021, Virtual, Online, Thailand, 5/08/21. https://doi.org/10.18653/v1/2021.gebnlp-1.1