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An Implemented Representation and Reasoning Systems for Creating and Exploiting Large Knowledge Bases of Narrative Information

An Implemented Representation and Reasoning Systems for Creating and Exploiting Large Knowledge Bases of Narrative Information
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Author(s): Gian Piero Zarri (Univeristy of Paris 4/ Sorbonne, France)
Copyright: 2008
Pages: 24
Source title: Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59904-951-9.ch078

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Abstract

In this chapter, we evoke first the ubiquity and the importance of the so-called ‘narrative’ information, showing that the usual ontological tools are unable to offer complete and reliable solutions for representing and exploiting this type of information. We then supply some details about NKRL (Narrative Knowledge Representation Language), a fully implemented knowledge representation and inferencing environment especially created for an ‘intelligent’ exploitation of narrative knowledge. The main innovation of NKRL consists in associating with the traditional ontologies of concepts an ‘ontology of events’, in other words, a new sort of hierarchical organization where the nodes correspond to n-ary structures representing formally generic classes of elementary events like ‘move a physical object’, ‘be present in a place’, or ‘send/receive a message’. More complex, second order tools based on the ‘reification’ principle allow one to encode the ‘connectivity phenomena’ like causality, goal, indirect speech, coordination, and subordination that, in narrative information, link together ‘elementary events’. The chapter includes a description of the inference techniques proper to NKRL, and some information about the last developments of this language.

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