GENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena

TL;DR

This paper introduces gENder-IT, a novel English-Italian challenge set designed to address natural gender phenomena in translation, aiding in resolving gender ambiguities in machine translation systems.

Contribution

It provides the first resource with word-level gender tags and multiple gendered translations for English-Italian, facilitating research on gender ambiguity resolution in MT.

Findings

Creates a new challenge set for gender resolution in translation

Provides annotated gender tags and multiple translations

Supports development of gender-aware MT systems

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.