Abstract : This paper proposes a methodology for comparing grammatical contrasts across categories with the tools of distributional semantics. After outlining why such a comparison is relevant to current theoretical work on gender and other morphosyntactic features, we present intrinsic and extrinsic predictability as instruments for analyzing semantic contrasts between pairs of words. We then apply our method to a dataset of gender pairs of French nouns and adjectives. We find that, while the distributional effect of gender is overall less predictable for nouns than for adjectives, it is heavily influenced by semantic properties of the adjectives.
Timothee Mickus, Olivier Bonami, Denis Paperno. Distributional Effects of Gender Contrasts Across Categories. Proceedings of the Society for Computation in Linguistics, Gaja Jarosz, 2019, 2, pp.174-184. ⟨10.7275/g11b-3s25⟩. ⟨hal-02062515⟩