Accession Number:

ADA458579

Title:

Cross-Document Coreference on a Large Scale Corpus

Descriptive Note:

Corporate Author:

MASSACHUSETTS UNIV AMHERST CENTER FOR INTELLIGENT INFORMATION RETRIEVAL

Personal Author(s):

Report Date:

2004-01-01

Pagination or Media Count:

9.0

Abstract:

In this paper, we will compare and evaluate the effectiveness of different statistical methods in the task of cross-document coreference resolution. We created entity models for different test sets and compare the following disambiguation and clustering techniques to cluster the entity models in order to create coreference chains Incremental Vector Space, KL-Divergence, Agglomerative Vector Space. Coreference analysis refers to the process of determining whether or not two mentions of entities refer to the same person Kibble and Deemter, 2000.

Subject Categories:

  • Linguistics
  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE