AUTOMATED KNOWLEDGE DERIVATION - DOMAIN-INDEPENDENT TECHNIQUES FOR DOMAIN-RESTRICTED TEXT SOURCES

This article provides a description of the major components of a syste m that builds and updates a knowledge base by extracting the knowledge from natural language text. The knowledge extraction is done in a dom ain-independent manner and does not rely on particular vocabulary or g rammar constructions. The only restriction is that the input text must be technical text from some specific problem domain. An important cap ability of the system is that it can bootstrap itself. That is, beginn ing with only a description of the types of object and relationships t o be stored in the knowledge base, the system can start with an empty knowledge base and build the knowledge base as it processes the text. The knowledge extraction system's success in extracting knowledge from various input texts was evaluated using scoring metrics reported by L ehnert and Sundheim [AI Mag., 12(3), 81-94 (1998)]. The initial result s indicate that the knowledge extraction mechanism is both effective a nd independent of a particular author's writing style or a particular domain. (C) 1995 John Wiley & Sons, Inc.