The use of figurative language is ubiquitous in natural language texts and it is a serious bottleneck in automatic text understanding. We address the problem of interpretation of logical metonymy, using a statistical method. Our approach originates from that of Lapata and Lascarides (2003), which generates a list of nondisambiguated interpretations with their likelihood derived from a corpus. W...

In this chapter, the main reference point in Yorick Wilks’s work is Wilks (1978). This extends his preferencebased semantics (Wilks, 1975) to handling metaphor. Wilks (1978) covers a number of issues that deserve fresh comment and that are central to problems about metaphor that are still unresolved—theoretically, let alone computationally. Also, the legacy of the 1978 work stretched through to...

Computational approaches to metonymy resolution have focused almost exclusively on the local context, especially the constraints placed on a potentially metonymic word by its grammatical collocates. We expand such approaches by taking into account the larger context. Our algorithm is tested on the data from the metonymy resolution task (Task 8) at SemEval 2007. The results show that incorporati...

This paper presents a method for deriving metonymic coercions from the knowledge available in WordNet. Two different classes of metonymies are inferred by using (1) lexico-semantic connections between concepts or (2) morphological cues and logical formulae defining lexical concepts. In both cases the derivation of metonymic paths is based on approximations of sortal constraints retrieved from W...

Logical metonymy combines an event-selecting verb with an entity-denoting noun (e.g., The writer began the novel), triggering a covert event interpretation (e.g., reading, writing). Experimental investigations of logical metonymy must assume a binary distinction between metonymic (i.e. eventselecting) verbs and non-metonymic verbs to establish a control condition. However, this binary distincti...

The correct identification of metonymies is not normally a problem for most people. For computers, things are different, however. In Natural Language Processing, metonymy recognition is therefore usually addressed with complex algorithms that rely on hundreds of labelled training examples. This paper investigates two approaches to metonymy recognition that dispense with this complexity, albeit ...

Many words carry multiple distinct but related senses. For example, a producer’s name (e.g., Picasso) can be metonymically extended to label products Picasso’s paintings) rarely refer other associated items paintbrushes). We test whether item-based linguistic experience is necessary for children’s acquisition of semantic generalizations. In Experiment 1, we present 4- 5-year-olds, 8- 9-year-old...

Logical metonymy resolution (begin a book → begin reading a book or begin writing a book) has traditionally been explained either through complex lexical entries (qualia structures) or through the integration of the implicit event via post-lexical access to world knowledge. We propose that recent work within the words-as-cues paradigm can provide a more dynamic model of logical metonymy, accoun...