Knowledge Representation with MESNET - A Multilayered Extended Semantic Network

Semantic Networks (SN) have been used in many applications, especially in the field of natural language understanding (NLU). The multflayered extended semantic network MESNET presented in this paper on the one hand follows the tradition of semantic networks (SN) starting with the work of Quillian (13). On the other hand, MESNET for the first time consequently and explicitly makes use of a multilayered structuring of a SN built upon an orthogonal system of dimensions and especially upon the distinction between an intensional and a preextensional layer. Furthermore, MESNET is based on a comprehensive system of classificatory means (sorts and features) as well as on semantically primitive relations and functions. It uses a relatively large but fixed inventory of representational means, encapsulation of concepts and a distinction between immanent and situative known edge. The whole complex of representational means is independent of special application domains. With regard to the representation of taxonomic knowledge, MESNET is characterized by the use of a multidimensional ontology. A first prototype of MESNET has been successfully applied for the meaning representation of natural language expressions in the system LINAS. In this paper, MESNET is presented in its double function as a cognitive model and as the target language for the semantic interpretation processes in NLU systems with emphasis on the ontological aspect of knowledge representation.