A Hybrid Approach for Relation Extraction Aimed at the Semantic Web

  • Lucia Specia
  • Enrico Motta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4027)


We present an approach for relation extraction from texts aimed to enrich the semantic annotations produced by a semantic web portal. The approach exploits linguistic and empirical strategies, by means of a pipeline method involving processes such as a parser, part-of-speech tagger, named entity recognition system, pattern-based classification and word sense disambiguation models, and resources such as an ontology, knowledge base and lexical databases. With the use of knowledge intensive strategies to process the input data and corpus-based techniques to deal both with unpredicted cases and ambiguity problems, we expect to accurately discover most of the relevant relations for known and new entities, in an automated way.


Semantic Relation Domain Ontology Semantic Annotation Word Sense Disambiguation Lexical Database 
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

  • Lucia Specia
    • 1
  • Enrico Motta
    • 1
  1. 1.Knowledge Media Institute & Centre for Research in ComputingThe Open UniversityMilton KeynesUK

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