A Typology of Lexical Analogy in WordNet

Analogy and metaphor are extremely knowledge-hungry processes, so one should question whether lightweight lexical ontologies like WordNet are sufficiently rich to support them. In this paper we argue that resources like WordNet are suited to the processing of certain kinds of lexical analogies and metaphors, for which we propose a spatially-motivated typology and a corresponding computational model. We identify two kinds of dimension that are important in lexical analogy ‐ lexicalized (taxonomic) dimensions and adhoc (goal-specific) dimensions ‐ and describe how these can be automatically identified, extracted and exploited in WordNet.