Knowledge Representation with MESNET {

Semantic Networks (SN) have been used in many applications , especially in the eld of natural language understanding (NLU). The multilayered extended semantic network MESNET presented in this paper on the one hand follows the tradition of SN starting with the work of Quillian 13]. On the other hand, MESNET for the rst 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 classiicatory means (sorts and features) as well as on semantically primitive relations and functions. It uses a relatively large but xed inventory of repre-sentational means, encapsulation of concepts and a distinction between immanent and situative knowledge. The whole complex of representa-tional means is independent of special application domains. At the same time, it is ne grained enough to allow for the diierentiation of all important nuances of meaning in the knowledge representation. MESNET has been especially developed for natural language understanding in question answering systems (QAS). A rst prototype is successfully used for the meaning representation of natural language expressions in the system LINAS 1. 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.