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<Paper uid="H92-1030">
  <Title>AUTOMATICALLY ACQUIRING PHRASE STRUCTURE USING DISTRIBUTIONAL ANALYSIS</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
ABSTRACT
</SectionTitle>
    <Paragraph position="0"> In this paper, we present evidence that the acquisition of the phrase structure of a natural language is possible without supervision and with a very small initial grammar. We describe a language learner that extracts distributional information from a corpus annotated with parts of speech and is able to use this extracted information to accurately parse short sentences. The phrase structure learner is part of an ongoing project to determine just how much knowledge of language can be learned solely through distributional analysis.</Paragraph>
  </Section>
class="xml-element"></Paper>