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<Paper uid="P02-1029">
  <Title>Inducing German Semantic Verb Classes from Purely Syntactic Subcategorisation Information</Title>
  <Section position="8" start_page="0" end_page="0" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> The paper presented the application of k-Means to the task of inducing semantic classes for German verbs. Based on purely syntactic probability distributions over verb subcategorisation frames, we obtained an intuitively plausible clustering of 57 verbs into 14 classes. The automatic clustering was evaluated against hand-constructed semantic verb classes.</Paragraph>
    <Paragraph position="1"> A series of post-hoc cluster analyses explored the influence of specific frames and frame groups on the coherence of the verb classes, and supported the tight connection between the syntactic behaviour of the verbs and their meaning components.</Paragraph>
    <Paragraph position="2"> Future work will concern the extension of the clustering experiments to a larger number of verbs, both for the scientific purpose of refining our understanding of the semantic and syntactic status of verb classes and for the more applied goal of creating a large, reliable and high quality lexical resource for German. For this task, we will need to further refine our verb classes, further develop the repertoire of syntactic frames which we use, perhaps improve the statistical grammar from which the frames were extracted and find techniques which allow us to selectively include such information about selectional preferences as is warranted by the availability of training data and the capabilities of clustering technology.</Paragraph>
  </Section>
class="xml-element"></Paper>