File Information

File: 05-lr/acl_arc_1_sum/cleansed_text/xml_by_section/concl/03/n03-2027_concl.xml

Size: 816 bytes

Last Modified: 2025-10-06 13:53:32

<?xml version="1.0" standalone="yes"?>
<Paper uid="N03-2027">
  <Title>Bayesian Nets in Syntactic Categorization of Novel Words</Title>
  <Section position="4" start_page="0" end_page="0" type="concl">
    <SectionTitle>
3 Conclusion
</SectionTitle>
    <Paragraph position="0"> Our approach shows promise as it is both probabilistic and outperforms existing statistical taggers on unknown words. We are especially encouraged by our performance on the WSJ and take this as evidence that our method has the potential to significantly improve PoS tagging of non-standard texts. In addition, our method has the advantage of being conceptually simple, fast, and flexible with respect to feature representation. We are currently investigating the performance of other DBN topologies on PoS tagging.</Paragraph>
  </Section>
class="xml-element"></Paper>
Download Original XML