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<Paper uid="C00-2138">
  <Title>Identifying Temporal Expression and its Syntactic Role Using FST and Lexical Data from Corpus</Title>
  <Section position="6" start_page="959" end_page="959" type="evalu">
    <SectionTitle>
5 Experimental Results
</SectionTitle>
    <Paragraph position="0"> bbr the {;xi}erinmnt al}out temporal exI}ressi{m, we extracted 300 senten{:es containing teml}oral expressi(ms from ETRI POS corlms. Tal}le 2 shows the r{'. null chunking sults from identit:ying temporal expressions and disaml/iguatil~g their syntactic functions. From the result in the table we see that the method is very effect, ive in that it very accurately identifies all tile temporal expressions aim assigns them syntactic tags. And, Table 2 shows the reduction resulted from chunking after temporal expression identification.</Paragraph>
    <Paragraph position="1"> We take into consideration the average numl)cr of head candidates for each word since our parser is dependency based one. The test was conducted on the tirst file (about 800 sentences) of KAIST tree-bank (Choict al. , 1994). The number was reduced by 51% in candidates compared to the system with no chunking, whMl makes pa.rsing efficient.</Paragraph>
    <Paragraph position="2"> Most of errors were caused by tile case where teinporal words have different syntactic roles under the same context. In this case, the global context such as the whole sentence or intcrscnt;cntial infornlation or sometimes very soi)histicated processing ix needed to resolve the prol)lem, l~br instance, '82 ~tycoTt(year) h, yco'njac-yi(now/Gl;N)' could be used two-.way. If the speech time is the year 1982, then h, yeou(fl, e-yi are conlbined with 82 nycon to represent time. Otherwise, 82 does not ino(til~y hycordac-yi, wlfich cannot be recognized only with the local context. Nevertheless, the system is promising in that generally it can ilnprove e\[flciency without losing accuracy which is crucial for the pracl;ical system.</Paragraph>
  </Section>
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