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<Paper uid="W06-2110">
  <Title>Automatic Identification of English Verb Particle Constructions using Linguistic Features</Title>
  <Section position="8" start_page="71" end_page="71" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we have proposed a method for identifying VPCs automatically from raw corpus data.</Paragraph>
    <Paragraph position="1"> We first used the RASP parser to identify VPC and verb-PP candidates. Then, we used analysis of the head nouns of the arguments of the head verbs to model selectional preferences, and in doing so, distinguish between VPCs and verb-PPs. Using TiMBL 5.1, we built a classifier which achieved an F-score of 97.4% at identifying frequent VPC examples. We also investigated the comparative performance of RASP at VPC identification.</Paragraph>
    <Paragraph position="2"> The principal drawback of our method is that it relies on the performance of RASP and we assume a pronoun resolution oracle to access the word senses of pronouns. Since the performance of such systems is improving, however, we consider our approach to be a promising, stable method of identifying VPCs.</Paragraph>
  </Section>
class="xml-element"></Paper>