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<Paper uid="N06-2024">
  <Title>NER Systems that Suit User's Preferences: Adjusting the Recall-Precision Trade-off for Entity Extraction</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We describe a method based on &amp;quot;tweaking&amp;quot; an existing learned sequential classifier to change the recall-precision tradeoff, guided by a user-provided performance criterion. This method is evaluated on the task of recognizing personal names in email and newswire text, and proves to be both simple and effective.</Paragraph>
  </Section>
class="xml-element"></Paper>