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<Paper uid="C00-2094">
  <Title>Using a Probabilistic Class-Based Lexicon for Lexical Ambiguity Resolution</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper presents the use of prot)abilistie class-based lexica tbr dismnbiguati(m in targetwoxd selection. Our method emlfloys nfinimal 1)llt; precise contextual information for disambiguation. That is, only information provided by the target-verb, enriched by the condensed information of a probabilistic class-based lexicon, is used. Induction of classes and fine-tuning to verbal arguments is done in an unsupervised manner by EM-lmsed clustering techniques. The method shows pronlising results in an evaluation on real-world translations.</Paragraph>
  </Section>
class="xml-element"></Paper>