Graph Ranking for Collective Named Entity Disambiguation
Ayman Alhelbawy, Robert Gaizauskas · 2014
Named Entity Disambiguation (NED) refers to the task of mapping different named entity mentions in running text to their correct interpretations in a specific knowledge base (KB). This paper presents a collective disambiguation approach us-ing a graph model. All possible NE candi-dates are represented as nodes in the graph and associations between different candi-dates are represented by edges between the nodes. Each node has an initial confidence score, e.g. entity popularity. Page-Rank is used to rank nodes and the final rank is combined with the initial confidence for candidate selection. Experiments on 27,819 NE textual mentions show the ef-fectiveness of using Page-Rank in con-junction with initial confidence: 87 % ac-curacy is achieved, outperforming both baseline and state-of-the-art approaches. 1