Refining instance coreferencing results using belief propagation

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. © 2008 Springer Berlin Heidelberg.