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<Paper uid="P98-1012">
  <Title>Entity-Based Cross-Document Coreferencing Using the Vector</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> 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 &amp;quot;the document boundary&amp;quot; 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-</Paragraph>
  </Section>
class="xml-element"></Paper>