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<Paper uid="M93-1011">
  <Title>GE-CMU: DESCRIPTION OF THE SHOGUN SYSTEM USEDFOR MUC- 5</Title>
  <Section position="8" start_page="115" end_page="115" type="concl">
    <SectionTitle>
SUMMARY AND CONCLUSIO N
</SectionTitle>
    <Paragraph position="0"> The examples and the analysis here are illustrative of the performance of the TIPSTER/SHOGUN syste m on MUC-5 . While the system has done well and continued to improve significantly, there are still quit e a number of problems that could be fixed to achieve better accuracy . On the other hand, the stead y improvement of the system and the high performance across languages are very gratifying, and the fact tha t we already seem close to human performance seems to bode well for the deployment of this technology.</Paragraph>
    <Paragraph position="1"> While research up to this point has emphasized interpretation and control issues, we see corpus analysi s and knowledge acquisition algorithms as being the key topics for further research and further progress . In this way, MUC-5 may represent a turning point from matters of structure to matters of scale, with most o f the necessary work on this type of task being broadening scope and scale . At the same time, we expect tha t simple but very challenging tasks will emerge that test some of the key algorithms that are required for dat a extraction.</Paragraph>
  </Section>
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