C. Beierle, U. Pletat, and R. Studer. Knowledge representation for natural language understanding: The L-LILOG approach. IEEE Transactions on Knowledge and Data Engineering, 5(3):386-401, June 1993.

Abstract:

Knowledge based natural language understanding requires the representation of various types of knowledge like linguistic knowledge, conceptual knowledge, taxonomic information, or knowledge about real world objects. Within LILOG, a natural language understanding project for German, the logic-based knowledge representation language L-LILOG is being used to represent both the semantic background knowledge as well as the information extracted from German texts. L-LILOG integrates frame-like feature-value descriptions used in the area of computational linguistics into an order-sorted predicate logic framework. We present the basic design principles of L-LILOG, give examples how it is used to model real world knowledge, describe the implementation of the first LILOG prototype, and provide a formal semantics definition.

Keywords:

Knowledge base, knowledge based system, knowledge representation, predicate logic, attribute-value descriptions, real world knowledge, natural language understanding, computational linguistics, prototype.