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<Paper uid="W03-1808">
  <Title>Verb-Particle Constructions and Lexical Resources</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
6 Discussion
</SectionTitle>
    <Paragraph position="0"> We investigated the identi cation of regular patterns among verb-particle constructions using dictionaries, corpora and Levin's classes. These results suggest that Levin's classes provide us with productive patterns of VPCs. Candidate VPCs generated from these classes can help us improve the coverage of current lexical resources, as shown in this investigation. We used the available lexical resources and corpus data to give us an indication of class productivity, and we used this information to rank these classes. We took a sample of those classes that were considered to be good predictors of valid VPCs, and these were further investigated, through human judgements, con rming their correspondence with productive patterns in VPCs. Some of the patterns can also be applied to other related particles (e.g. the resultative pattern and locative/directional particles), but even using a small set of particles it was possible to considerably extended the coverage of these lexical resources.</Paragraph>
    <Paragraph position="1"> More investigation into the productivity of the lower ranked classes is needed since the domain being considered was restricted to the combined resources, and we only considered a candidate VPC to be valid if it was listed in them. For instance, in a manual analysis of the combinations involving the class of Roll verbs (class 51.3.1, bounce, drift,  drop, oat, glide, move, roll, slide, swing) most of the verb-particles generated were considered acceptable.4 In relation to the A+C+E-VPCs, we found that 64% of these combinations are not listed. The use of corpora signi cantly reduces this problem, so that when we also consider the BNC-VPCs, the results are much better, with 80.5% of the combinations being listed. But for some classes, such as those involving motion, not even the addition of corpus data helps, and a great proportion of the VPCs are not attested, even though most of the combinations are considered acceptable by native speakers. Thus, a more wide investigation using human judgement and a larger set of VPCs would be necessary, also using the World Wide Web as corpus.</Paragraph>
    <Paragraph position="2"> Nonetheless, these results are encouraging and conrm that these classes provide us with good predictors of VPC acceptability. Thus, the use of these classes to automatically generate verb-particle constructions, based on groups of verbs and particles presents a reasonable way of improving coverage of existing lexical resources.</Paragraph>
  </Section>
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