Tracking Mentions to Put Them in Chains

We present a novel statistical approach for tracking mentions of an entity in a document. Mentions are scored pairwise by a relevance score and then clustered into chains representing single entities. Our approach handles all mentions of proper names, nominals and pronouns, but in this work we restrict our attention to the five mention types concerning ACE (Automatic Content Extraction). Our results show that this method achieves an ACE value score of 88.8% on true mentions.

By: Abraham Ittycheriah, Malgorzata Stys

Published in: RC22998 in 2003


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