SANAPHOR: Ontology-Based Coreference Resolution

  • Roman ProkofyevEmail author
  • Alberto Tonon
  • Michael Luggen
  • Loic Vouilloz
  • Djellel Eddine Difallah
  • Philippe Cudré-Mauroux
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9366)


We tackle the problem of resolving coreferences in textual content by leveraging Semantic Web techniques. Specifically, we focus on noun phrases that coreference identifiable entities that appear in the text; the challenge in this context is to improve the coreference resolution by leveraging potential semantic annotations that can be added to the identified mentions. Our system, SANAPHOR, first applies state-of-the-art techniques to extract entities, noun phrases, and candidate coreferences. Then, we propose an approach to type noun phrases using an inverted index built on top of a Knowledge Graph (e.g., DBpedia). Finally, we use the semantic relatedness of the introduced types to improve the state-of-the-art techniques by splitting and merging coreference clusters. We evaluate SANAPHOR on CoNLL datasets, and show how our techniques consistently improve the state of the art in coreference resolution.


Noun Phrase Computational Linguistic Semantic Annotation Name Entity Recognition Inverted Index 
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

  • Roman Prokofyev
    • 1
    Email author
  • Alberto Tonon
    • 1
  • Michael Luggen
    • 1
  • Loic Vouilloz
    • 2
  • Djellel Eddine Difallah
    • 1
  • Philippe Cudré-Mauroux
    • 1
  1. 1.eXascale InfolabUniversity of FribourgFribourgSwitzerland
  2. 2.Linguistics DepartmentUniversity of FribourgFribourgSwitzerland

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