Task-dependent aspects of knowledge acquisition: A case study in a technical domain

Abstract

This paper summarises principles of manual acquisition of conceptual graphs which evolved within the framework of a natural language processing system and are now enriched and elaborated to facilitate the construction of a larger knowledge base. Our conventions provide the mapping between language structures (at syntactic and semantic levels) and conceptual structures. The task-dependent aspects of our approach are clearly presented. We Mso discuss the problems of finding suitable domain descriptions to be used as acquisition sources. Finally, we evaluate the manual and automatic knowledge acquisition from the perspective of our current experience.