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<Paper uid="C00-2175">
  <Title>Comparing two trainable grammatical relations finders</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Grammatical relationships (Glls) form an important level of natural language processing, but different sets of ORs are useflfl for different purposes. Theretbre, one may often only have time to obtain a small training corpus with the desired GI1. annotations. On su&amp; a small training corpus, we compare two systems. They use difl'erent learning tedmiques, but we find that this difference by itself only has a minor effect.</Paragraph>
    <Paragraph position="1"> A larger factor is that iLL English, a different GI/. length measure appears better suited for finding simple m:gument GI{s than ~br finding modifier GRs. We also find that partitioning the data ma W help memory-based learning.</Paragraph>
  </Section>
class="xml-element"></Paper>