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<Paper uid="W06-2208">
  <Title>Expanding the Recall of Relation Extraction by Bootstrapping</Title>
  <Section position="8" start_page="61" end_page="61" type="relat">
    <SectionTitle>
5 Related Work
</SectionTitle>
    <Paragraph position="0"> SPL is a similar approach to DIPRE (Brin, 1998) DIPRE uses a pre-defined simple regular expression to identify argument values. Therefore, it can also suffer from the type error problem described above. LRPLavoids this problem by using the Relation NER.</Paragraph>
    <Paragraph position="1"> LRPL is similar to SnowBall(Agichtein, 2005), which employs a generic NER, and reported that most errors come from NER errors. Because our evaluation showed that Relation NERworks better than generic NER,a combination of Relation NER and SnowBall can make a better result in other settings. 3 (Collins and Singer, 1999) and (Jones, 2005) describe self-training and co-training methods for Named Entity Classification. However, the problem of NEC task, where the boundary of entities are given by NP chunker or parser, is different from NE tagging task. Because the boundary of an entity is often different from a NP boundary, the technique can not be used for our purpose; &amp;quot;Microsoft CEO Steve Ballmer&amp;quot; is tagged as a single noun phrase.</Paragraph>
  </Section>
class="xml-element"></Paper>