Lexically evaluating ontology triples generated automatically from texts

  • Authors:
  • Peter Spyns;Marie-Laure Reinberger

  • Affiliations:
  • STAR Lab, Vrije Universiteit Brussel, Brussel, Belgium;CNTS, University of Antwerp, Wilrijk, Belgium

  • Venue:
  • ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
  • Year:
  • 2005

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Abstract

Our purpose is to present a method to lexically evaluate the results of extracting in an unsupervised way material from text corpora to build ontologies. We have worked on a legal corpus (EU VAT directive) consisting of 43K words. The unsupervised text miner has produced a set of triples. These are to be used as preprocessed material for the construction of ontologies from scratch. A quantitative scoring method (coverage, accuracy, recall and precision metrics resulting in a 38.68%, 52.1%, 9.84% and 75.81% scores respectively) has been defined and applied.