The Narrative Knowledge Representation Language, specifically implemented to deal with non-fictional narrative of an economic interest. ‘Classical’ ontologies are largely sufficient to provide a static, a priori definition of the concepts and of their properties. This is no more true when we consider the dynamic behavior of the concepts, i.e., we want to describe their mutual relationships when they take part in some concrete action, situation etc. (‘events’). NKRL deals with this problem by adding to the usual ontology of concept an ‘ontology of events’, a new sort of hierarchical organization where the nodes, called ‘templates’, represent general classes of events like “move a physical object”, “be present in a place”, “produce a service”, “send/receive a message”, etc.
Published in Chapter:
Using Rules in the Narrative Knowledge Representation Language (NKRL) Environment
Gian Piero Zarri (University Paris Est and LISSI Laboratory, France)
Copyright: © 2009
|Pages: 26
DOI: 10.4018/978-1-60566-402-6.ch003
Abstract
NKRL is a semantic language expressly designed to deal with all sort of ‘narratives’, in particular with those (‘non-fictional narratives’) of an economic interest. From a knowledge representation point of view, its main characteristics consists in the use of two different sorts of ontologies, a standard, binary ontology of concepts, and an ontology of n-ary templates, where each template corresponds to the formal representation of a class of elementary events. Rules in NKRL correspond to high-level reasoning paradigms like the search for causal relationships or the use of analogical reasoning. Given i) the conceptual complexity of these paradigms, and ii) the sophistication of the underlying representation language, rules in NKRL cannot be implemented in a (weak) ‘inference by inheritance’ style but must follow a powerful ‘inference by resolution’ approach. After a short reminder about these two inference styles, and a quick introduction of the NKRL language, the chapter describes in some depth the main characteristics of the NKRL inference rules.