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<Paper uid="W02-1028">
  <Title>A Bootstrapping Method for Learning Semantic Lexicons using Extraction Pattern Contexts</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> In recent years, several algorithms have been developed to acquire semantic lexicons automatically or semi-automatically using corpus-based techniques.</Paragraph>
    <Paragraph position="1"> For our purposes, the term semantic lexicon will refer to a dictionary of words labeled with semantic classes (e.g., \bird&amp;quot; is an animal and \truck&amp;quot; is a vehicle). Semantic class information has proven to be useful for many natural language processing tasks, including information extraction (Rilo and Schmelzenbach, 1998; Soderland et al., 1995), anaphora resolution (Aone and Bennett, 1996), question answering (Moldovan et al., 1999; Hirschman et al., 1999), and prepositional phrase attachment (Brill and Resnik, 1994). Although some semantic dictionaries do exist (e.g., WordNet (Miller, 1990)), these resources often do not contain the specialized vocabulary and jargon that is needed for speci c domains. Even for relatively general texts, such as the Wall Street Journal (Marcus et al., 1993) or terrorism articles (MUC-</Paragraph>
  </Section>
class="xml-element"></Paper>