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<Paper uid="P98-2251">
  <Title>Predicting Part-of-Speech Information about Unknown Words using Statistical Methods</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper examines the feasibility of using statistical methods to train a part-of-speech predictor for unknown words. By using statistical methods, without incorporating hand-crafted linguistic information, the predictor could be used with any language for which there is a large tagged training corpus. Encouraging results have been obtained by testing the predictor on unknown words from the Brown corpus.</Paragraph>
    <Paragraph position="1"> The relative value of information sources such as affixes and context is discussed. This part-of-speech predictor will be used in a part-of-speech tagger to handle out-of-lexicon words.</Paragraph>
  </Section>
class="xml-element"></Paper>