Multiple property models of lexical categories

Abstract

In multiple property models of lexical categories, the assignment of a word to a lexical category is determined by a set of properties associated with that category. Specifically, if a word displays a sufficient number of properties associated with a given category, it will be assigned to that category. The current article critically evaluates multiple property models of lexical categories. In particular, it focuses on a multiple property model recently developed by Aarts (Syntactic gradience: The nature of grammatical indeterminacy, Oxford University Press, 2007b) and a variety of other such models. It is argued that multiple property models encounter problems in four key areas. Firstly, they struggle to determine an appropriate set of lexical categories and to provide coherent accounts of the nature and function of such categories. Secondly, they encounter difficulties in determining the properties that define categories and in determining features of properties such as whether they should be weighted or not. Thirdly, a variety of problems arise when multiple property models combine words, properties and categories together. Finally, multiple property models fail to account for crosslinguistic data. It is concluded that multiple property models do not provide viable accounts of lexical categories.