Work

Entity-based cross-document coreferencing using the Vector Space Model

Year: 1998

Type: conference-paper

Abstract: 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 MUC-6 (within document) coreference task.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.3115/980845.980859

Authors: Amit Bagga, Breck Baldwin

Institutions: Duke University, University of Pennsylvania

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: International Business Machines Corporation, University of Pennsylvania

OpenAlex ID: W2113227740

FWCI: 2.527

Cites: 4

Cited by: 550

Related to: 10