Designing and Evaluating Patterns for Ontology Enrichment from Texts

  • Nathalie Aussenac-Gilles
  • Marie-Paule Jacques
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4248)


Pattern-based approaches for knowledge identification in texts assume that linguistic regularities always characterise the same kind of knowledge, such as semantic relations. We report the experimental evaluation of a large set of patterns using an ontology enrichment tool: Camélé on. Results underline the strong corpus influence on the patterns efficiency and on their meaning. This influence confirms two of the hypotheses that motivated to define Camélé on as a support used in a supervised process: (1) patterns and relations must be adapted to each project; (2) human interpretation is required to decide how to report in the ontology the pieces of knowledge identified with patterns.


Semantic Relation Coloured Word Knowledge Identification Precision Rate Relation Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nathalie Aussenac-Gilles
    • 1
  • Marie-Paule Jacques
    • 2
  1. 1.Institut de Recherche en Informatique de Toulouse (IRIT) – CNRS, UPSToulouseFrance
  2. 2.Équipe de Recherche en Syntaxe et Sémantique (ERSS)CNRS, Maison de la Recherche, UTMToulouseFrance

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