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<Paper uid="W04-0855">
  <Title>UBB system at Senseval3</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
Word Sense Disambiguation (WSD) is the pro-
</SectionTitle>
    <Paragraph position="0"> cess of identifying the correct meanings of words in particular contexts (Manning and Schutze, 1999). It is only an intermediate task in NLP, like POS tagging or parsing. Examples of flnal tasks are Machine Translation, Information Extraction or Dialogue systems. WSD has been a research area in NLP for almost the beginning of this fleld due to the phenomenon of polysemy that means multiple related meanings with a single word (Widdows, 2003). The most important robust methods in WSD are: machine learning methods and dictionary based methods. While for English exist some machine readable dictionaries, the most known being Word-Net (Christiane Fellbaum, 1998), for Romanian until now does not exist any. Therefore for our application we used the machine learning approach. null</Paragraph>
  </Section>
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