gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena
Eva Vanmassenhove, Johanna Monti · 2021
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.