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<Paper uid="W97-0202">
  <Title>Experience in WordNet Sense Tagging in the Wall Street Journal</Title>
  <Section position="9" start_page="10" end_page="10" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> Data manually annotated with lexical semantics clearly has many applications in NLP. This paper shared our experience in manual annotation of WordNet senses in the Wall Street Journal Treebank corpus. WordNet proved to be a valuable and useful tool. Its wide range of senses made possible a highly specific level of tagging. WordNet's structure, with the alignment of hierarchical information and the addition of synsets and sample sentences, was especially helpful. We have made some suggestions for consistently identifying certain uses of verbs and for representing tags, and have shared some guidelines from our annotation instructions for identifying idioms in the corpus.</Paragraph>
  </Section>
class="xml-element"></Paper>