Towards Semantic Annotation Supported by Dependency Linguistics and ILP

  • Jan Dědek
Conference paper

DOI: 10.1007/978-3-642-17749-1_20

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6497)
Cite this paper as:
Dědek J. (2010) Towards Semantic Annotation Supported by Dependency Linguistics and ILP. In: Patel-Schneider P.F. et al. (eds) The Semantic Web – ISWC 2010. ISWC 2010. Lecture Notes in Computer Science, vol 6497. Springer, Berlin, Heidelberg


In this paper we present a method for semantic annotation of texts, which is based on a deep linguistic analysis (DLA) and Inductive Logic Programming (ILP). The combination of DLA and ILP have following benefits: Manual selection of learning features is not needed. The learning procedure has full available linguistic information at its disposal and it is capable to select relevant parts itself. Learned extraction rules can be easily visualized, understood and adapted by human. A description, implementation and initial evaluation of the method are the main contributions of the paper.


Semantic Annotation Dependency Linguistics Inductive Logic Programming Information Extraction Machine Learning 

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jan Dědek
    • 1
  1. 1.Department of Software EngineeringCharles UniversityPragueCzech Republic

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