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        <title>gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena</title>
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            <namePart type="given">Marta</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena
%A Vanmassenhove, Eva
%A Monti, Johanna
%Y Costa-jussa, Marta
%Y Gonen, Hila
%Y Hardmeier, Christian
%Y Webster, Kellie
%S Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F vanmassenhove-monti-2021-gender
%X 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.
%R 10.18653/v1/2021.gebnlp-1.1
%U https://aclanthology.org/2021.gebnlp-1.1
%U https://doi.org/10.18653/v1/2021.gebnlp-1.1
%P 1-7

Markdown (Informal)

[gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena](https://aclanthology.org/2021.gebnlp-1.1) (Vanmassenhove & Monti, GeBNLP 2021)

• gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena (Vanmassenhove & Monti, GeBNLP 2021)

ACL

• Eva Vanmassenhove and Johanna Monti. 2021. gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena. In Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing, pages 1–7, Online. Association for Computational Linguistics.