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<Paper uid="W06-2001">
  <Title>Multilingual Extension of a Temporal Expression Normalizer using Annotated Corpora</Title>
  <Section position="7" start_page="7" end_page="7" type="concl">
    <SectionTitle>
5 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper we have presented an automatic extension of a rule-based approach to TEs recognition and normalization. The procedure is based on building temporal models for new languages starting from previously defined ones. This procedure is able to fill the gap left by machine learning systems that, up to date, are still far from providing acceptable performance on this task. As results illustrate, the proposed methodology (even though with a lower performance with respect to language-specific systems) is a viable and effective solution for a rapid and automatic porting of an existing system to new languages.</Paragraph>
  </Section>
class="xml-element"></Paper>