Introduction

If current natural language understanding systems reason about the world at all, they generally maintain a strict division between the parsing processes and the representation that supports general reasoning about the world. The parsing processes, which include syntactic analysis, some semantic interpretation, and possibly some discourse processing, I will call structural processing, because these processes are primarily concerned with analyzing and determining the linguistic structure of individual sentences. The part of the system that involves representing and reasoning about the world or domain of discourse I will call the knowledge representation. The goal of this chapter is to examine why these two forms of processing are separated, to determine the current advantages and limitations of this approach, and to look to the future to attempt to identify the inherent limitations of the approach. I will point out some fundamental problems with the models as they are defined today and suggest some important directions of research in natural language and knowledge representation. In particular, I will argue that one of the crucial issues facing future natural language systems is the development of knowledge representation formalisms that can effectively handle ambiguity.

It has been well recognized since the early days of the field that representing and reasoning about the world are crucial to the natural language understanding task. Before we examine the main issue of the chapter in detail, let us consider some of the issues that have long been identified as demonstrating this idea. Knowledge about the world can be seen to be necessary in almost every aspect of the understanding task.