Entity-Based Cross-Document Coreferencing Using the Vector Space Model

Cross-document coreference occurs when the same person, place, event, or concept is discussed in more than one text source. Computer recognition of this phenomenon is important because it helps break "the document boundary" by allowing a user to examine information about a particular entity from multiple text sources at the same time. In this paper we describe a cross-document coreference resolution algorithm which uses the Vector Space Model to resolve ambiguities between people having the same name. In addition, we also describe a scoring algorithm for evaluating the cross-document coreference chains produced by our system and we compare our algorithm to the scoring algorithm used in the MUC6 (within document) coreference task.

• Type: Conference
• Year: 1998
• Where: ACL
• Authors: Amit Bagga, Breck Baldwin
• Keywords: ACL 1998, ACL 2007, Cross-document Coreference, Scoring Algorithm, Text Sources