Proceedings of the Annual Meeting of the Cognitive Science Society

Patterns of crosslinguistic variation in the expression of wordmeaning are informative about semantic organization, but mostmethods to study this are labor intensive and obscure the gra-dient nature of concepts. We propose an automatic method forextracting crosslinguistic co-categorization patterns from par-allel texts, and explore the properties of the data as a potentialsource for automatically creating semantic representations forcognitive modeling. We focus on indefinite pronouns, com-paring our findings against a study based on secondary sources(Haspelmath 1997). We show that using automatic methods onparallel texts contributes to more cognitively-plausible seman-tic representations for a domain.