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. I. Levels of Expectation The primary emphasis that has been given to the study of the sentence by linguists and computational linguists has brought about some peculiar ways of studying natural language. Clearly people do not understand nor generate sentences in isolation. It has been in fashion among linguists who like to attack other linguists ' ideas of grammaticality, to refute a statement of ungrammaticality by finding a situation in which the supposed ungrammatical sentence makes sense. Lakoff (6) has recently noted the need for using presupposition- sentence pairs before one can discuss grammaticality. It has long been our assertion that, while it seems reasonable that linguists who are studying grammaticality should take context into account, the study of grammaticality itself seems a bit misguided (see Schank (11)). What would seem to be more reasonable Is to realize that people talk in order to communicate