Implicational Molecules: A Method for Extracting Meaning from Input Sentences

Abstract

A generally overlooked possibility for extracting pragmatic meaning from sentence inputs is discussed. This possibility draws upon tha psychology of the subjective attribution of causes to stimulus events. Application to the design of conversational programs is feasible, although the present work concerns application to the simulation of a belief system. Simple sentences known by the system are grouped into categorical types. An implicational ia a meaningful aet of sentence types with linked elements, for example: A does X, X causes Y, A wants Y. One important way in which meaning can ba described to an input sentence is to use it as the basis for a molecule which ia then filled by other information in tha system. This notion is defined mathematically, and a programming algorithm outlined. The possibility of recursive use of a molecule-filling routine gives tha process heuristic overtones.