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LODifier: Generating Linked Data from Unstructured Text

  • Isabelle Augenstein
  • Sebastian Padó
  • Sebastian Rudolph
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7295)

Abstract

The automated extraction of information from text and its transformation into a formal description is an important goal in both Semantic Web research and computational linguistics. The extracted information can be used for a variety of tasks such as ontology generation, question answering and information retrieval. LODifier is an approach that combines deep semantic analysis with named entity recognition, word sense disambiguation and controlled Semantic Web vocabularies in order to extract named entities and relations between them from text and to convert them into an RDF representation which is linked to DBpedia and WordNet. We present the architecture of our tool and discuss design decisions made. An evaluation of the tool on a story link detection task gives clear evidence of its practical potential.

Keywords

Resource Description Framework Name Entity Recognition Word Sense Disambiguation Entity Recognition Link Open Data 
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 2012

Authors and Affiliations

  • Isabelle Augenstein
    • 1
  • Sebastian Padó
    • 1
  • Sebastian Rudolph
    • 2
  1. 1.Department of Computational LinguisticsUniversität HeidelbergGermany
  2. 2.Institute AIFBKarlsruhe Institute of TechnologyGermany

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