<?xml version="1.0" standalone="yes"?>
<Paper uid="W97-0901">
  <Title>Reuse of a Proper Noun Recognition System in Commercial and Operational NLP Applications</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> Fast and accurate name recognition products are only now coming onto the market. SRA's proprietary product, NameTag, has been reused in many applications in recent and ongoing efforts, including multilingual information retrieval and browsing, text clustering, and assistance to manual text indexing.</Paragraph>
    <Paragraph position="1"> In the following paper, we report on our experience in embedding name recognition in these, three specific applications, as well as the mutual impacts that occur, both on the algorithmic level and in the role that name recognition plays in user interaction with a system. In the course of this, we touch upon various interactions between proper name recognition and machine translation (MT), as well as the role of accurate name recognition in improving the performance of word segmentation algorithms needed for languages such as Japanese. Name recognition clearly offers added value when integrated with other algorithms and systems, but the latter also affect the way in which name recognition is performed, specifically the choice of high-recall or high-precision strategies. But first, we discuss the relevant features of NameTag.</Paragraph>
  </Section>
class="xml-element"></Paper>