Modeling natural language metaphors with an answer set programming framework

Abstract

Metaphors are natural language constructions that play an important role in the way human beings communicate knowledge and understand the world. Some formal philosophers such as Searle and Lakoff claim that the semantic analysis of expressions that involve fictional stories and metaphors are examples of the inadequacy of using predicate logic for the analysis of the meaning of language. D’Hanis proposes that using predicate logic in combination of non-monotonic reasoning is possible to interpret metaphorical expressions. In this paper, we introduce an approach for modelling metaphorical thinking using a particular form of logic programming called answer set programming (ASP). ASP essentially enhances the logical apparatus of predicate calculus by introducing mechanisms such as negation as a failure that enable the system to accomplish non-monotonic reasoning. We show that using ASP is possible to model the meaning of some expressions involving metaphorical constructions and the implementation of metaphorical reasoning mechanisms that could be a great addition to any knowledge-based application.