<?xml version="1.0" standalone="yes"?>
<Paper uid="W97-0317">
  <Title>Attaching Multiple Prepositional Phrases: Generalized Backed-off Estimation</Title>
  <Section position="10" start_page="153" end_page="153" type="concl">
    <SectionTitle>
6 Conclusions
</SectionTitle>
    <Paragraph position="0"> The backed-off estimate has been demonstrated to work successfully for single PP attachment, but the sparse data problem renders it impractical for use in more complex constructions such as multiple PP attachment; there are too many configurations, too many head words, too few training examples. In this paper we have demonstrated, however, that the relatively rich training data obtained for the first preposition can be exploited in attaching subsequent PPs. The algorithm incrementally fixes each preposition into the configuration and the more informative PP1 training data is exploited to settle the competition for possible attachments for each subsequent preposition. Performance is considerably better than both chance and the naive baseline technique. The generalized backed-off estimation approach which we have presented constitutes a practical solution to the problem of multiple PP disambiguation. This further suggests that backed-off estimation may be successfully integrated into more general syntactic disambiguation systems.</Paragraph>
  </Section>
class="xml-element"></Paper>