A Qualitative Similarity Framework for the Interpretation of Natural Language Similarity Expressions

Abstract

AbstractIn this paper, a representational framework is presented featuring a qualitative notion of similarity. It is aimed at issues of natural language semantics, in particular the semantics of expressions of similarity and sameness and their role in comparison and ad-hoc kind formation. The framework makes use of attribute spaces, which are well-established in AI and also in some branches of natural language semantics, e.g., frame-based approaches (Barsalou 1992). What distinguishes attribute spaces and representations as proposed in this paper is the idea of systems of predicates on attribute spaces corresponding to predicates on the domain. On the worldy side, a domain includes a set of relevant predicates talking about individuals. These predicates have counterparts on the representational side talking about points of an attribute space. Counterpart predicates are required to be consistent with their originals; more precisely, they have to agree in truth-value on the set of positive and negative exemplars thereby approximating the original predicates. Moreover, counterpart predicates will be assumed to have convex and open extensions. This system facilitates a qualitative notion of similarity which is suited to account for the meaning of natural language similarity expressions and, furthermore, their role in comparison and ad-hoc kind formation.