Finding the Conceptual Content and Intention in an Utterance in Natural Language Conversation

Abstract

The conceptual dependency analyzer described in the first IJCAI (8) has been modified so as to function more conceptually with less reliance on syntactic rules. In order to have an analyzer be conceptually driven, it is necessary for the system to know what it is looking for. That is, it must make predictions as to what can follow conceptually at any point in the analysis. This paper discusses the extension of conceptual prediction to include predictions based on context and the structure of the memory model that operates with the analyzer. Such predictions make use of relations between conceptual actions and the implications of those actions. This enables the conceptual analyzer to discover not only the conceptual content of an utterance but also the intention of that utterance in context. We are concerned with the extraction of the conceptual content both explicit and implicit in an utterance in order to analyze effectively in an interactive conversational situation.