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SHELDON: Semantic Holistic FramEwork for LinkeD ONtology Data

  • Diego Reforgiato Recupero
  • Andrea Giovanni Nuzzolese
  • Sergio Consoli
  • Aldo Gangemi
  • Valentina Presutti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8982)

Abstract

SHELDON is a framework that builds upon a machine reader for extracting RDF graphs from text so that the output is compliant to Semantic Web and Linked Data patterns. It extends the current human-readable web by using semantic best practices and technologies in a machine-processable form. Given a sentence in any language, it provides different semantic tasks as well as nice visualization tools which make use of the JavaScript infoVis Toolkit and a knowledge enrichment component on top of RelFinder. The system can be freely used at http://wit.istc.cnr.it/stlab-tools/sheldon.

Keywords

Sentiment Analysis Word Sense Disambiguation Semantic Task Semantic Role Label Discourse Representation Theory 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Diego Reforgiato Recupero
    • 1
    • 2
  • Andrea Giovanni Nuzzolese
    • 1
    • 2
  • Sergio Consoli
    • 1
    • 2
  • Aldo Gangemi
    • 1
    • 2
  • Valentina Presutti
    • 1
    • 2
  1. 1.STLab-ISTC Consiglio Nazionale delle RicercheCataniaItaly
  2. 2.LIPN Sorbonne-CitéUniversité de Paris-13VilletaneuseFrance

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