Conference article

Figurative language poses a serious challenge to NLP systems. The use of idiomatic and metaphoric expressions is not only extremely widespread in natural language; many figurative expressions; in particular idioms; also behave idiosyncratically. These idiosyncrasies are not restricted to a non-compositional meaning but often also extend to syntactic properties; selectional preferences etc. To deal appropriately with such expressions; NLP tools need to detect figurative language and assign the correct analyses to non-literal expressions. While there has been quite a bit of work on determining the general ‘idiomaticity’ of an expression (type-based approaches); this only solves part of the problem as many expressions; such as break the ice or play with fire; can also have a literal; perfectly compositional meaning (e.g. break the ice on the duck pond). Such expressions have to be disambiguated in context (token-based approaches). Token-based approaches have received increased attention recently. In this talk; I will present an unsupervised method for token-based idiom detection. The method exploits the fact that well-formed texts exhibit lexical cohesion; i.e. words are semantically related to other words in the context. I will show how cohesion can be modelled and how the cohesive structure can be used to distinguish literal and idiomatic usages and even detect newly coined figurative expressions.

Discourse; Figurative Language; Token-Based Idiom Detection