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<Paper uid="W04-0837">
  <Title>Using Automatically Acquired Predominant Senses for Word Sense Disambiguation</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> The first sense heuristic which is often used as a baseline for supervised WSD systems outperforms many of these systems which take surrounding context into account (McCarthy et al., 2004). The high performance of the first sense baseline is due to the skewed frequency distribution of word senses. Even systems which show superior performance to this heuristic often make use of the heuristic where evidence from the context is not sufficient (Hoste et al., 2001).</Paragraph>
    <Paragraph position="1"> The first sense heuristic is a powerful one. Using the first sense listed in SemCor on the SENSEVAL-2 English all-words data we obtained the results given in table 1, (where the PoS was given by the gold-standard data in the SENSEVAL-2 data itself). 1 Recall is lower than precision because there</Paragraph>
  </Section>
class="xml-element"></Paper>