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<Paper uid="W06-0117">
  <Title>Posts and Telecommunications yuandong@bupt.edu.cn</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper presents two word segmentation (WS) systems and a named entity recognition (NER) system in France Telecom R&amp;D Beijing. The one system of WS is for open tracks based on n-gram language model and another one is for closed tracks based on maximum entropy approach. The NER system uses a hybrid algorithm based on Class-based language model and rule-based knowledge. These systems are all augmented with a set of post-processors.</Paragraph>
  </Section>
class="xml-element"></Paper>