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<Paper uid="P98-1016">
  <Title>Redundancy: helping semantic disambiguation</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> The construction of a Lexical Knowledge Base (LKB), if performed automatically (or semiautomatically), attempts at extracting knowledge from text. The extraction can be viewed as a learning process. Simplicity, clarity and redundancy of the information given in the source text are key features for a successful acquisition of knowledge. We assume success is attained when a sentence from the source text expressed in natural language can be transformed into an unambiguous internal representation. Using a conceptual graph (CG) representation (Sowa, 1984) of sentences means that a successful acquisition of knowledge corresponds to transforming each sentence from the source text into a set of unambiguous concepts (correct word senses found) and unambiguous relations (correct semantic relations between concepts).</Paragraph>
    <Paragraph position="1"> This paper will look at the idea of making good use of the redundancy found in a text to help the knowledge acquisition task. Things are not always understood when they are first encountered. A sentence expressing new knowledge might be ambiguous (at the level of the concepts it introduces and/or at the level of the semantic relations between those concepts). A search through previously acquired knowledge might help disambiguate the new sentence or it might not. A repetition of the exact same sentence would be of no help, but a slightly different format of expression might reveal necessary aspects for the comprehension. This is the avenue explored in this paper which will unfold as follows. Section 2 will present briefly a possible good source of knowledge and a gathering/clustering technique. Section 3 will present how the redundancy resulting from the clustering process can be used in solving some types of semantic ambiguity. Section 4 will emphasize the importance of semantic relations for the process of semantic disambiguation. Section 5 will conclude.</Paragraph>
  </Section>
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