Hierarchical refinement and representation of the causal relation

Bibliographic Data

ID20395347
AuthorsCaroline Barrière (University of Ottawa, corresponding author)
Year2002
Volume8
Issue1
Pages91-111
Publication date2002-07-05
Open AccessNo
TypeARTICLE
VenueTerminology International Journal of Theoretical and Applied Issues in Specialized Communication (JOURNAL)
Journal identifiersISSN: 0929-9971 • E-ISSN: 1569-9994
PublisherJohn Benjamins Publishing Company (PUBLISHER • NL)
DOI10.1075/term.8.1.05bar
OpenAlexW2046145328
LanguageEN
Citations received3

This research looks at the complexity inherent in the causal relation and the implications for its representation in a Terminological Knowledge Base (TKB). Supported by a more general study of semantic relation hierarchies, a hierarchical refinement of the causal relation is proposed. It results from a manual search of a corpus which shows that it efficiently captures and formalizes variations expressed in text. The feasibility of determining such categorization during automatic extraction from corpora is also explored. Conceptual graphs are used as a representation formalism to which we have added certainty information to capture the degree of certainty surrounding the interaction between two terms involved in a causal relation

Categorization · Certainty · Cognition · Data mining · Epistemology · Natural language processing · Semantic relation · Computer Science · linguistics and terminology studies · Natural Language Processing Techniques · Philosophy · Psychology · Semantic Web and Ontologies · Artificial Intelligence · Theoretical Computer Science

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