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<Paper uid="P98-2177">
  <Title>Statistical Models for Unsupervised Prepositional Phrase Attachment</Title>
  <Section position="9" start_page="1084" end_page="1084" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> The unsupervised algorithm for prepositional phrase attachment presented here is the only algorithm in the published literature that can significantly outperform the baseline without using data derived from a treebank or parser.</Paragraph>
    <Paragraph position="1"> The accuracy of our technique approaches the accuracy of the best supervised methods, and does so with only a tiny fraction of the supervision. Since only a small part of the extraction heuristic is specific to English, and since part-of-speech taggers and morphology databases are widely available in other languages, our approach is far more portable than previous approaches for this problem. We successfully demonstrated the portability of our approach by applying it to the prepositional phrase attachment task in the Spanish language.</Paragraph>
  </Section>
class="xml-element"></Paper>