Uncovering Probabilistic Implications in Typological Knowledge Bases

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The study of linguistic typology is rooted in the implications we find between linguistic features, such as the fact that languages with object-verb word ordering tend to have postpositions. Uncovering such implications typically amounts to time-consuming manual processing by trained and experienced linguists, which potentially leaves key linguistic universals unexplored. In this paper, we present a computational model which successfully identifies known universals, including Greenberg universals, but also uncovers new ones, worthy of further linguistic investigation. Our approach outperforms baselines previously used for this problem, as well as a strong baseline from knowledge base population.
Original languageEnglish
Title of host publicationProceedings of the 57th Annual Meeting of the Association for Computational Linguistics
PublisherAssociation for Computational Linguistics
Publication date2019
Pages3924–3930
DOIs
Publication statusPublished - 2019
Event57th Annual Meeting of the Association for Computational Linguistics - Florence, Italy
Duration: 1 Jul 20191 Jul 2019

Conference

Conference57th Annual Meeting of the Association for Computational Linguistics
LandItaly
ByFlorence,
Periode01/07/201901/07/2019

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