Building Embedded Conceptual Parsers
(Table of Contents)

This is a version of Dr. Will Fitzgerald's Dissertation, Building Embedded Conceptual Parsers. The conversion was made semi-automatically, so there are some errors that crept in, as it was converted from FrameMaker version 4.0 for the Macintosh, to MIF format, to RTF format, to HTML. Chapter 3, for example, would not convert from MIF at all. Oh well.

Abstract

This dissertation describes how to build conceptual parsers (that is, natural language understanding systems built on semantic and pragmatic principles) that are embedded into application programs. A new architecture for building such parsers, indexed concept parsing, is described. Indexed concept parsing is a case-based reasoning approach to parsing, in which underlying target concepts (that is, those conceptual representations of the application program identified as important to recognize) are associated with sets of index concepts. Each index concept is associated with sets of phrasal patterns. At run time, the parser looks for phrasal patterns in input text, and the index concepts recognized thereby are used to appraise the best matching target concepts. The architecture defines a range of parsers, in which the complexity of the index concept representations can vary according to the needs of the application program: index concepts can be key words, synonym sets, representations in an abstraction hierarchy, or representations in a partonomic hierarchy. Indexed concept parsing was developed to build parsers for Casper, an interactive learning environment designed to teach customer service representatives how to solve customer problems, and TransAsk, a multimedia system for transportation planners. Indexed concept parsing proved robust (for example, the Casper parser had an accuracy rate ranging from 83-96%), yet required minimal knowledge representation. A methodology for building an indexed concept parser is given, and evaluation metrics are described. Another parser, based on Direct Memory Access Parsing (DMAP), and developed for the Creanimate biology tutor, is also described, as well as a DMAP parser for Casper. Indexed concept parsing and DMAP are contrasted as architectures for building embedded conceptual parsers.