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<Paper uid="C00-2101">
  <Title>Learning Semantic-Level Information Extraction Rules by Type-Oriented ILP</Title>
  <Section position="9" start_page="703" end_page="703" type="concl">
    <SectionTitle>
8 Conclusions and Remarks
</SectionTitle>
    <Paragraph position="0"> This paper described a use of semantic representations for generating information extraction rules by applying a type-oriented ILP system.</Paragraph>
    <Paragraph position="1"> Experiments were conducted on the data generated fi'om 100 news articles in the domain of new product release. The results showed very high precision, recall of 67-82% without data correction and 70-88% recall with correct semantic representations. The extraction of five different pieces of information showed good results. This indicates that our learner RHB + has a high potential in IE tasks.</Paragraph>
  </Section>
class="xml-element"></Paper>