Refining Instance Coreferencing Results Using Belief Propagation

Authors:
Andriy Nikolov;Victoria Uren;Enrico Motta;Anne Roeck
Affiliations:
Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK
Venue:
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
Year:
2008

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Abstract

The problem of coreference resolution (finding individuals, which describe the same entity but have different URIs) is crucial when dealing with semantic data coming from different sources. Specific features of Semantic Web data (ontological constraints, data sparseness, varying quality of sources) are all significant for coreference resolution and must be exploited. In this paper we present a framework, which uses Dempster-Shafer belief propagation to capture these features and refine coreference resolution results produced by simpler string similarity techniques.