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<Paper uid="P98-2177">
  <Title>Statistical Models for Unsupervised Prepositional Phrase Attachment</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We present several unsupervised statistical models for the prepositional phrase attachment task that approach the accuracy of the best supervised methods for this task. Our unsupervised approach uses a heuristic based on attachment proximity and trains from raw text that is annotated with only part-of-speech tags and morphological base forms, as opposed to attachment information. It is therefore less resource-intensive and more portable than previous corpus-based algorithm proposed for this task. We present results for prepositional phrase attachment in both English and Spanish. null</Paragraph>
  </Section>
class="xml-element"></Paper>