Proceedings of the Annual Meeting of the Cognitive Science Society

In previous work, we identified a method for automatically deriving possible rules of plausible inference from a set of relations, and determined that the transitivity of underlying characteristics of the relations was a significant factor in predicting the plausibility of inferences generated from these rules. Recent work by other researchers has also focused on identifying these kinds of characteristics and examining their role in the ability to predict plausibility. W e examine these sets of characteristics and conclude that those factors that preserve transitivity provide most of the power of these systems. W e then show how inferences can be used to determine the intended semantics, and thus the appropriate set of representational features, of a relation.