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Automatic Acquisition of Lexical Knowledge about Multiword Predicates Afsaneh Fazly Doctor of Philosophy Graduate Department of Computer Science University of Toronto 2007 A multiword predicate is the combination of a predicate (often a verb) with one or more of its arguments, that together form a single unit of predicative meaning. We focus on a broad class of multiword predicates, in which a verb combines with a noun in the direct object position (e.g., give a groan and shoot the breeze). The semantic interpretation of such multiword predicates involves a certain degree of idiosyncrasy; moreover, they are crosslinguistically frequent and appear in all text genres. Hence, they pose a great challenge to the current models of natural language processing. Most existing computational models treat multiword predicates as syntactically-dependent word sequences or collocations. Such a treatment ignores other important characteristics of these constructions, reflected in their distinct lexical and syntactic behaviour. Nonetheless, cues from the lexicosyntactic properties of multiword predicates have often been used in linguistic and psycholinguistic studies to explain their peculiar semantic behaviour. On the one hand, simple statistical approaches that only draw on the frequency of multiword predicates fail to account for much of the syntactic and semantic behaviour of these constructions. On the other hand, linguistic theories provide generalizations about the behaviour of multiword predicates that can be augmented with probabilistic knowledge about language in use. The main goal of the present study is to propose ways of combining the predictive power of linguistic theories with the coverage and robustness of statistical techniques to acquire linguistically-plausible and reliable corpus-drawn knowledge about multiword predicates.