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1 RCEAL - Research Centre for English and Applied Linguistics 2 LaTTICe - LaTTiCe - Langues, Textes, Traitements informatiques, Cognition - UMR 8094 3 Computer Laboratory Cambridge

Abstract : This paper introduces a novel method for joint unsupervised aquisition of verb subcategorization frame (SCF) and selectional preference (SP) information. Treating SCF and SP induction as a multi-way co-occurrence problem, we use multi-way tensor factorization to cluster frequent verbs from a large corpus according to their syntactic and semantic behaviour. The method extends previous tensor factorization approaches by predicting whether a syntactic argument is likely to occur with a verb lemma (SCF) as well as which lexical items are likely to occur in the argument slot (SP), and integrates a variety of lexical and syntactic features, including co-occurrence information on grammatical relations not explicitly represented in the SCFs. The SCF lexicon that emerges from the clusters achieves an F-score of 68.7 against a gold standard, while the SP model achieves an accuracy of 77.8 in a novel evaluation that considers all of a verb-s arguments simultaneously.

Author: Tim Van de Cruys - Laura Rimell - Thierry Poibeau - Anna Korhonen -



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