Abstract
A methodology for knowledge acquisition from terminology databases is presented. The methodology outlines how the content of a terminology database can be mapped onto a knowledge base with a minimum of human intervention. Typically, terms are defined and elaborated by terminologists by using sentences that have a common syntactic and semantic structure. It has been argued that in defining terms, terminologists use a local grammar and that this local grammar can be used to parse the definitions. The methodology has been implemented in a program called DEARSys (Definition Analysis and Representation System), that reads definition sentences and extracts new concepts and conceptual relations about the defined terms. The linguistic component of the system is a parser for the sublanguage of terminology definitions that analyses a definition into its logical form, which in turn is mapped onto a frame-based representation. The logical form is based on first-order logic (FOL) extended with untyped lambda calculus. Our approach is data-driven and domain independent; it has been applied to definitions of various domains. Experiments were conducted with human subjects to evaluate the information acquired by the system. The results of the preliminary evaluation were encouraging.