Resumen de La lucha contra el terrorismo y la delincuencia organizada: Una visión desde la lingüística y la ingeniería del conocimiento
The aim of Natural Language Processing is to create computational systems for the production and comprehension of language by machines. In this regard, symbolic approaches to language put forth conceptual models which represent both common and specialised knowledge. This paper describes the ontological modelling of the “collective criminal agent” and its implementation in FunGramKB, a knowledge base for language processing and artificial reasoning. More specifically, the study focuses on the conceptual definition of three terminological units from the domains of terrorism and organised crime: cartel, oriented cluster, and terrorist cell. The main assumption is that ontological modelling applied to language technologies can play a major role in combating a variety of security threats to today’s society.1
