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<Paper uid="P98-2247">
  <Title>Detecting Verbal Participation in Diathesis Alternations</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We present a method for automatically identifying verbal participation in diathesis alternations. Automatically acquired subcategorization frames are compared to a hand-crafted classification for selecting candidate verbs. The minimum description length principle is then used to produce a model and cost for storing the head noun instances from a training corpus at the relevant argument slots. Alternating sub-categorization frames are identified where the data from corresponding argument slots in the respective frames can be combined to produce a cheaper model than that produced if the data is encoded separately. I.</Paragraph>
  </Section>
class="xml-element"></Paper>