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<Paper uid="M98-1018">
  <Title>NYU: Description of the MENE Named Entity System as Used in MUC-7</Title>
  <Section position="8" start_page="2" end_page="2" type="concl">
    <SectionTitle>
CONCLUSIONS AND FUTURE WORK
</SectionTitle>
    <Paragraph position="0"> MENE is a very new, and, we feel, still immature system. Work started on the system in October, 1997, and the system described abovewas not largely in place until mid-February, 1998 #28about three weeks before the evaluation#29. We believe that we can push the score of the MENE-only system higher by adding long-range reference-resolution features to allow MENE to pro#0Ct from terms and their acronyms which it has correctly tagged elsewhere in the corpus. Wewould also like to explore compound features #28i.e. feature A #0Cres if features B and C both #0Cre#29 and more sophisticated methods of feature selection.</Paragraph>
    <Paragraph position="1"> Nevertheless, we believe that we have already demonstrated some very useful results. Within-domain scores for MENE-only were good and this system is highly portable as wehave already demonstrated with our result on upper-case English text. Porting MENE can be done with very little e#0Bort: our result on running MENE with only lexical and section features shows that it isn't even necessary to provide it with dictionaries to generate an acceptable result. We intend to port the system to Japanese NE to further demonstrate MENE's #0Dexibility.</Paragraph>
    <Paragraph position="2"> However, we believe that the within-domain results on combining MENE with other systems are some of the most intriguing. We would hypothesize that, given su#0Ecient training data, any handcoded system would bene#0Ct from having its output passed to MENE as a #0Cnal step. MENE also opens up new avenues for collaboration whereby di#0Berent organizations could focus on di#0Berent aspects of the problem of N.E.</Paragraph>
    <Paragraph position="3"> recognition with the maximum entropy system acting as an arbitrator. MENE also o#0Bers the prospect of achieving very high performance with very little e#0Bort. Since MENE starts out with a fairly high base score just on its own, we speculate that a MENE user could then construct a hand-coded system which only focused on MENE's weaknesses, while skipping the areas in which MENE is already strong.</Paragraph>
    <Paragraph position="4"> Finally, one can imagine a large corporation or government agency acquiring licenses to several di#0Berent N.E. systems, generating some training data, and then combining it all under a MENE-like system. Wehave shown that this approach can yield performance which is competitive with that of a human tagger.</Paragraph>
  </Section>
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