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<Paper uid="C92-2082">
  <Title>Automatic Acquisition of Hyponyms ~om Large Text Corpora</Title>
  <Section position="5" start_page="0" end_page="0" type="concl">
    <SectionTitle>
4 Conclusions
</SectionTitle>
    <Paragraph position="0"> We have described a low-cost approach for automatic acquisition of semantic lexical relations from uurestricted text. This method is meant to provide an incremental step toward the larger goals of natural language processing. Our approach is complementary to statistically based approaches that find semantic relations between terms, iu that ours requires a single specially expressed instance of a relation while the others require a statistically significant number of generally expressed relations. We've shown that our approach is also useful as a critiquing component for existing knowledge bases and lexicons.</Paragraph>
    <Paragraph position="1"> We plan to test the pattern discovery algorithm on more relations and on languages other than English (depending on the corpora available). We would also like to do some analysis of the noun phrases that are acquired, and to explore the effects of various kinds of modifiers on the appropriateness of the noun phrase.</Paragraph>
    <Paragraph position="2"> We plan to do this in the context of analyzing environmental impact reports.</Paragraph>
    <Paragraph position="3"> Acknowledgements. This work was supported in part by an internship at tile Xerox Palo Alto Research Center and in part by the University of California and Digital Equipment Corporation under Digital's flag-AcrEs DE COLING-92, NANTES, 23-28 ^o~-r 1992 5 4 4 PRoc. OF COLING-92. NANTES, Auo. 23-28, 1992 ship research project Sequoia 2000: Large Capacity Object Servers to Support Global Change Research.</Paragraph>
  </Section>
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