Lapata, M. and A. Lascarides [2003] A Probabilisitic Account of Logical Metonymy, Computational Linguistics, 29(2), pp263--317.
In this paper we investigate logical metonymy, i.e., constructions involving a form of semantic type coercion, in that the semantic type of the argument of a word in syntax appears to be different from the semantic type of 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 suggest a rich and complex theory of composition on the syntax/semantics interface (e.g., Pustejovsky, 1995). But the generative devices which are used to model logical metonymy typically fail to exhaustively describe 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 which provides a ranking on the set of possible interpretations. We identify lexical semantic information automatically by exploiting the consistent correspondences between surface syntactic cues and lexical meaning. We evaluate our results against paraphrase judgements elicited experimentally from humans, and show that the model's ranking of meanings correlates reliably with human intuitions: meanings that are found highly probable by the model are also rated as plausible by the human subjects.
@article{lapata:lascarides:2003,
author = {Mirella Lapata and Alex Lascarides},
year = {2003},
title = {A Probabilistic Account of Logical Metonymy},
journal = {Computational Linguistics},
volume = {29},
number = {2},
pages = {263--317},
publisher = {MIT Press}
}