Automatic acquisition of syntactic verb classes with basic resources

摘要

This paper describes a methodology aimed at grouping Catalan verbs according to their syntactic behavior. Our goal is to acquire a small number of basic classes with a high level of accuracy, using minimal resources. Information on syntactic class, expensive and slow to compile by hand, is useful for any NLP task requiring specific lexical information. We show that it is possible to acquire this kind of information using only a POS-tagged corpus. We perform two clustering experiments. The first one aims at classifying verbs into transitive, intransitive and verbs alternating with a se-construction. Our system achieves an average 0.84 F-score, for a task with a 0.33 baseline. The second experiment aims at further distinguishing among pure intransitives and verbs bearing a prepositional object. The baseline for the task is 0.51 and the upperbound 0.98. The system achieves an average 0.88 F-score.