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<Paper uid="N04-1002">
  <Title>Cross-Document Coreference on a Large Scale Corpus</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> 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:</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
Incremental Vector Space
KL-Divergence
Agglomerative Vector Space
</SectionTitle>
      <Paragraph position="0"/>
    </Section>
  </Section>
class="xml-element"></Paper>