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<Paper uid="W06-0124">
  <Title>Boosting for Chinese Named Entity Recognition</Title>
  <Section position="7" start_page="152" end_page="152" type="evalu">
    <SectionTitle>
4 Results
</SectionTitle>
    <Paragraph position="0"> Table 1 presents the results obtained on the MSRA and CityU development test set. Table 2 presents theresultsobtainedontheMSRA,CityUandLDC test sets. These numbers greatly underrepresent what could be expected from the boosting model, since we only used one-third of MSRA and CityU training corpora due to limitations of the boosting software. Another problem for the LDC corpus was training/testing mismatch: we did not train any models at all with the LDC training corpus, which was the only training set annontated with geopolitical entities (GPE). Instead, for the LDC test set, we simply used the system trained on the MSRA corpus. Thus, when we consider the geopolitical entity (GPE), our low overall F-measure on the LDC test set cannot be interpreted meaningfully.3 Even so, using only one-third of the training data, the results on the MSRA and CityU test sets are reasonable: 75.07 and 80.51 overall F-measures were obtained on the MSRA and CityU test sets, respectively.</Paragraph>
  </Section>
class="xml-element"></Paper>