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<Paper uid="W06-0202">
  <Title>Comparing Information Extraction Pattern Models</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Several recently reported techniques for the automatic acquisition of Information Extraction (IE) systems have used dependency trees as the basis of their extraction pattern representation. These approaches have used a variety of pattern models (schemes for representing IE patterns based on particular parts of the dependency analysis). An appropriate model should be expressive enough to represent the information which is to be extracted from text without being overly complicated. Four previously reported pattern models are evaluated using existing IE evaluation corpora and three dependency parsers. It was found that one model, linked chains, could represent around 95% of the information of interest without generating an unwieldy number of possible patterns.</Paragraph>
  </Section>
class="xml-element"></Paper>