In this article we investigate logical metonymy, that is, constructions in which the argument of a word in syntax appears to be different from that argument in logical form (e.g., enjoy the book means enjoy reading the book, and easy problem means a problem that is easy to solve). The systematic variation in the interpretation of such constructions suggests a rich and complex theory of composition on the syntax/semantics interface. Linguistic accounts of logical metonymy typically fail to describe exhaustively all the possible interpretations, or they don't rank those interpretations in terms of their likelihood. In view of this, we acquire the meanings of metonymic verbs and adjectives from a large corpus and propose a probabilistic model that provides a ranking on the set of possible interpretations. We identify the interpretations automatically by exploiting the consistent correspondences between surface syntactic cues and meaning. We evaluate our results against paraphrase judgments elicited experimentally from humans and show that the model's ranking of meanings correlates reliably with human intuitions.

Verbs such as enjoy in the student enjoyed the book exhibit logical metonymy: enjoy is interpreted as enjoy reading. Theoretical work (Pustejovsky, 1991, 1995) predicts that this interpretation can be influenced by intra-sentential context, e.g., by the subject of enjoy. In this article, we test this prediction using a completion experiment and find that the interpretation of a metonymic verb is influenced by the semantic role of its subject. We present a Bayesian model that accounts for the interpretation of logical metonymy and achieves a good fit on our experimental data. We show that the parameters of the model can be estimated from completion data or from corpus data.

Thi s dissertation in its entirety is the result of my own work, and includes nothing which is the outcome of work done in collaboration. This dissertation does not exceed 86,000 words (pennission has been granted from the Board of Graduate Studies to exceed 80,000 words). This thesis is under copyright at the University Library, Cambridge, UK. This research combines elements in pragmatics, sociolinguistics, and cogml1ve linguistics, using empirical data to contribute to our understanding of th e processing of polite discourse. One hundred and five hours of spontaneous conversational data produced by native Cypriot Greek speakers of both sexes and of various ages and socio-economic backgrounds were recorded in various setti ngs. The serni-phonological transcription of realisations of offers and requests yielded a corpus of 2,189 observations. Extra-linguistic variables considered during the analysis of these data included the interl ocutors ' sex, age, and social class, the rel ationship between them,

The use of figurative language is ubiquitous in natural language texts and it is a serious bottleneck in automatic text understanding. A system capable of interpreting figurative expressions would be an invaluable addition to the real-world natural language processing (NLP) applications that need to access semantics, such as machine translation, opinion mining, question answering and many others. In this paper we focus on one type of figurative language, logical metonymy, and present a computational model of its interpretation bringing together statistical techniques and the insights from linguistic theory. Compared to previous approaches this model is both more informative and more accurate. The system produces sense-level interpretations of metonymic phrases and then automatically organises them into conceptual classes, or roles, discussed in the majority of linguistic literature on the phenomenon.

Intra-sentential context effects on the interpretation of logical metonymy ⋆