Building ontological meaning in a lexico-conceptual knowledge base

Resumen

Framed within the world of Artificial Intelligence, and more precisely within the project FunGramKB, i.e. a user-friendly environment for the semiautomatic construction of a multipurpose lexico-conceptual knowledge base for Natural Language Processing systems, the aim of this paper is two-fold. Firstly, we shall provide a necessarily non-exhaustive theoretical discussion of FunGramKB in which we will introduce the main elements that make up its Ontology (i.e. Thematic Frames, Meaning Postulates, different types of concepts, etc.). Secondly, we will describe the meticulous process carried out by knowledge engineers when populating this conceptually-driven Ontology. In doing so, we shall examine various examples belonging to the domain of �change� or #TRANSFORMATION (in the COREL notation), in an attempt to show how conceptual knowledge can be modeled in for Artificial Intelligence purposes.