<?xml version="1.0" standalone="yes"?>
<Paper uid="P05-2001">
  <Title>Hybrid Methods for POS Guessing of Chinese Unknown Words</Title>
  <Section position="9" start_page="4" end_page="4" type="evalu">
    <SectionTitle>
5.3 Results for the Combined Model
</SectionTitle>
    <Paragraph position="0"> To evaluate the combined model, we first define the upper bound of the precision for the model as the number of unknown words tagged correctly by at least one of the three models divided by the total number of unknown words. The upper bound is 91.10% for the training data and 91.39% for the test data. Table 7 reports the results for the combined model. The overall precision of the model reaches 89.32% in the training data and 89.00% in the test data, close to the upper bounds.</Paragraph>
  </Section>
class="xml-element"></Paper>