Paper: Latent Variable Models of Selectional Preference

ACL ID P10-1045
Title Latent Variable Models of Selectional Preference
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

This paper describes the application of so-called topic models to selectional pref- erence induction. Three models related to Latent Dirichlet Allocation, a proven method for modelling document-word co- occurrences, are presented and evaluated on datasets of human plausibility judge- ments. Compared to previously proposed techniques, these models perform very competitively, especially for infrequent predicate-argument combinations where they exceed the quality of Web-scale pre- dictions while using relatively little data.