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<Paper uid="W97-0312">
  <Title>Learning to Tag Multilingual Texts Through Observation</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper describes RoboTag, an advanced prototype for a machine learning-based multilingual information extraction system. First, we describe a general client/server architecture used in learning from observation. Then we give a detailed description of our novel decision-tree tagging approach. RoboTag performance for the proper noun tagging task in English and Japanese is compared against human-tagged keys and to the best hand-coded pattern performance (as reported in the MUC and MET evaluation results). Related work and future directions are presented. null</Paragraph>
  </Section>
class="xml-element"></Paper>