<?xml version="1.0" standalone="yes"?>
<Paper uid="N01-1007">
  <Title>Unsupervised Learning of Name Structure From Coreference Data</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We present two methods for learning the structure of personal names from unlabeled data.</Paragraph>
    <Paragraph position="1"> The rst simply uses a few implicit constraints governing this structure to gain a toehold on the problem  |e.g., descriptors come before rst names, which come before middle names, etc.</Paragraph>
    <Paragraph position="2"> The second model also uses possible coreference information. We found that coreference constraints on names improve the performance of the model from 92.6% to 97.0%. We are interested in this problem in its own right, but also as a possible way to improve named entity recognition (by recognizing the structure of different kinds of names) and as a way to improve noun-phrase coreference determination.</Paragraph>
  </Section>
class="xml-element"></Paper>