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<Paper uid="W99-0201">
  <Title>Cross-Document Event Coreference: Annotations, Experiments, and Observations Amit Bagga General Electric Company CRD</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
2 Introduction
</SectionTitle>
    <Paragraph position="0"> Events form the backbone of the reasons why people communicate to one another. News is interesting and important because it describes actions, changes of state and new relationships between individuals.</Paragraph>
    <Paragraph position="1"> While the communicative importance of described events is evident, the phenomenon has proved difficult to recognize and manipulate in automated ways (example: MUC information extraction efforts).</Paragraph>
    <Paragraph position="2"> We began this research program by developing algorithms to determine whether two mentions of a name, example &amp;quot;John Smith&amp;quot;, in different documents actually referred to the same individual in the world. The system that we built was quite successful at resolving cross-document entoty coreference (Bagga, 98b). We, therefore, decided to extend the system so that it could handle events as well. Our goal was to determine whether events in separate documents, example &amp;quot;resignations&amp;quot;, referred to the same event in the world (is it the same person resigning from the same company at the same time).</Paragraph>
    <Paragraph position="3"> This new classof coreference has proved to be more challenging.</Paragraph>
    <Paragraph position="4"> Below we will present our approach and results as follows: First we discuss how this research is different from Information Extraction and Topic Detection and Tracking. Then we present the core algorithm for cross document person coreference and our method of scoring the the system's output. The method for determining event reference follows with presentation and discussion of results. We finish with an interannotator agreement experiment and future work.</Paragraph>
  </Section>
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