Knowledge Extraction Based on Discourse Representation Theory and Linguistic Frames

  • Valentina Presutti
  • Francesco Draicchio
  • Aldo Gangemi
Conference paper

DOI: 10.1007/978-3-642-33876-2_12

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7603)
Cite this paper as:
Presutti V., Draicchio F., Gangemi A. (2012) Knowledge Extraction Based on Discourse Representation Theory and Linguistic Frames. In: ten Teije A. et al. (eds) Knowledge Engineering and Knowledge Management. EKAW 2012. Lecture Notes in Computer Science, vol 7603. Springer, Berlin, Heidelberg

Abstract

We have implemented a novel approach for robust ontology design from natural language texts by combining Discourse Representation Theory (DRT), linguistic frame semantics, and ontology design patterns. We show that DRT-based frame detection is feasible by conducting a comparative evaluation of our approach and existing tools. Furthermore, we define a mapping between DRT and RDF/OWL for the production of quality linked data and ontologies, and present FRED, an online tool for converting text into internally well-connected and linked-data-ready ontologies in web-service-acceptable time.

Keywords

frame detection discourse representation theory robust ontology design knowledge extraction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Valentina Presutti
    • 1
  • Francesco Draicchio
    • 1
  • Aldo Gangemi
    • 1
  1. 1.STLabISTC - CNRRomaItaly

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