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<Paper uid="C02-1126">
  <Title>Recovering latent information in treebanks</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Many recent statistical parsers rely on a preprocessing step which uses hand-written, corpus-specific rules to augment the training data with extra information. For example, head-finding rules are used to augment node labels with lexical heads. In this paper, we provide machinery to reduce the amount of human e ort needed to adapt existing models to new corpora: first, we propose a flexible notation for specifying these rules that would allow them to be shared by di erent models; second, we report on an experiment to see whether we can use Expectation-Maximization to automatically fine-tune a set of hand-written rules to a particular corpus.</Paragraph>
  </Section>
class="xml-element"></Paper>