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<Paper uid="W01-0704">
  <Title>Semantic Pattern Learning Through Maximum Entropy-based WSD techniquea0</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> Semantic patterns, as defined in this method, configure a system to add a new information source to Natural Language Processing (NLP) tasks. To obtain these semantic patterns, it is necessary to count on different tools. On the one hand, a full parser must make a syntactic analysis of the text.</Paragraph>
    <Paragraph position="1"> This parsing will allow the selection of the different syntactic functional elements such as subject, direct object (DObj) and indirect object (IObj).</Paragraph>
    <Paragraph position="2"> On the other hand, a WSD tool must provide the correct sense in order to ensure the appropriate selection of the ontological concept associated to each word. Finally, with the parsing and the correct sense of each word, the pattern extraction method will form and store ontological pairs that define the semantic behaviour of each sentence.</Paragraph>
  </Section>
class="xml-element"></Paper>