Making Lexical Ontologies Functional and Context-Sensitive

Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 57–64, Prague, Czech Republic, June 2007. c⃝2007 Association for Computational Linguistics Making Lexical Ontologies Functional and Context-Sensitive Tony Veale Computer Science and Informatics University College Dublin Ireland tony.veale@ucd.ie Yanfen Hao Computer Science and Informatics University College Dublin Ireland yanfen.hao@ucd.ie Abstract Human categorization is neither a binary nor a context-free process. Rather, some con- cepts are better examples of a category than others, while the criteria for category mem- bership may be satisfied to different degrees by different concepts in different contexts. In light of these empirical facts, WordNet’s static category structure appears both exces- sively rigid and unduly fragile for process- ing real texts. In this paper we describe a syntagmatic, corpus-based approach to re- defining WordNet’s categories in a func- tional, gradable and context-sensitive fash- ion. We describe how the diagnostic prop- erties for these definitions are automati- cally acquired from the web, and how the increased flexibility in categorization that arises from these redefinitions offers a ro- bust account of metaphor comprehension in the mold of Glucksberg’s (2001) the- ory of category-inclusion. Furthermore, we demonstrate how this competence with figu- rative categorization can effectively be gov- erned by automatically-generated ontologi- cal constraints, also acquired from the web. 1 Introduction Linguistic variation across contexts is often symp- tomatic of ontological differences between contexts. These observable variations can serve as valuable clues not just to the specific senses of words in con- text (e.g., see Pustejovsky, Hanks and Rumshisky, 2004) but to the underlying ontological structure it- self (see Cimiano, Hotho and Staab, 2005). The most revealing variations are syntagmatic in nature, which is to say, they look beyond individual word forms to larger patterns of contiguous usage (Hanks, 2004). In most contexts, the similarity between chocolate, say, and a narcotic like heroin will mea- gerly reflect the simple ontological fact that both are kinds of substances; certainly, taxonomic measures of similarity as discussed in Budanitsky and Hirst (2006) will capture little more than this common- ality. However, in a context in which the addictive properties of chocolate are very salient (e.g., an on- line dieting forum), chocolate is more likely to be categorized as a drug and thus be considered more similar to heroin. Look, for instance, at the simi- lar ways in which these words can be used: one can be ”chocolate-crazed” or ”chocolate-addicted” and suffer ”chocolate-induced” symptoms (e.g., each of these uses can be found in the pages of Wikipedia). In a context that gives rise to these expressions, it is unsurprising that chocolate should appear altogether more similar to a harmful narcotic. In this paper we computationally model this idea that language use reflects category structure. As noted by De Leenheer and de Moor (2005), ontolo- gies are lexical representations of concepts, so we can expect the effects of context on language use to closely reflect the effects of context on ontolog- ical structure. An understanding of the linguistic ef- fects of context, …

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