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<Paper uid="W06-0203">
  <Title>Parser Errors</Title>
  <Section position="4" start_page="1" end_page="1" type="intro">
    <SectionTitle>
DFG PI 154/10-1
</SectionTitle>
    <Paragraph position="0"> (http://www.coli.uni-saarland.de/projects/corte/) be supplemented by automatic acquisition methods. The same is true for large-scale advanced information access: Extensive conceptual indexation of even a fraction of all court decisions published in one year seems hardly possible without automatic support. However there has been relatively little research on the use of natural language processing for this purpose (exceptions are (Lame 2005) and (Saias and Quaresma 2005)).</Paragraph>
    <Paragraph position="1"> In this paper we look at the use of computational linguistic analysis techniques for information access and ontology learning within the legal domain. We present a rule-based method for extracting and analyzing definitions from parsed text, and evaluate this method on a corpus of about 6000 German court decisions within the field of environmental law. We then report on an experiment exploring the use of our extraction results to improve the quality of text-based ontology learning from noun-adjective bigrams. We will start however with a general discussion of the role that definitions play in legal language.</Paragraph>
  </Section>
class="xml-element"></Paper>