{"pk":26672,"title":"Unsupervised learning of VerbNet argument structure","subtitle":null,"abstract":"The relationship between a verb and the syntactic frames in which it can appear has been closely studied by psychol-ogists and linguists. Research suggests that the semantics of a verb and its arguments determine the verb’s syntactic frames,but various theories (Levin & Hovav, 2005) disagree on the nature and complexity of these relationships, in part because mostinvestigations have focused on a small subset of verbs that may not generalize. Investigating the semantic and syntactic rela-tionships present in larger sets of verbs would provide more substantial evidence for evaluating and selecting theories of verbargument structure. We report on initial analyses of the 6000+ verbs and 280+ syntactic frames of VerbNet (Kipper et al., 2008),the largest English verb syntax resource available, using nonparametric Bayesian methods (e.g. Shafto et al., 2006) for clusteranalysis and dimensionality reduction.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Member Abstracts","is_remote":true,"remote_url":"https://escholarship.org/uc/item/22j3x6s6","frozenauthors":[{"first_name":"Jesse","middle_name":"","last_name":"Mu","name_suffix":"","institution":"Boston College","department":""},{"first_name":"Timothy","middle_name":"","last_name":"O’Donnell","name_suffix":"","institution":"Massachusetts Institute of Technology","department":""},{"first_name":"Joshua","middle_name":"","last_name":"Hartshorne","name_suffix":"","institution":"Boston College","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2016-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26672/galley/16308/download/"}]}