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<Paper uid="P06-2007">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics N Semantic Classes are Harder than Two</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We show that we can automatically classify semantically related phrases into 10 classes. Classification robustness is improved by training with multiple sources of evidence, including within-document cooccurrence, HTML markup, syntactic relationships in sentences, substitutability in query logs, and string similarity. Our work provides a benchmark for automatic n-way classification into WordNet's semantic classes, both on a TREC news corpus and on a corpus of substitutable search query phrases.</Paragraph>
  </Section>
class="xml-element"></Paper>