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<Paper uid="W06-3503">
  <Title>Understanding Complex Natural Language Explanations in Tutorial Applications[?]</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We describe the WHY2-ATLAS intelligent tutoring system for qualitative physics that interacts with students via natural language dialogue. We focus on the issue of analyzing and responding to multi-sentential explanations. We explore an approach that combines a statistical classifier, multiple semantic parsers and a formal reasoner for achieving a deeper understanding of these explanations in order to provide appropriate feedback on them.</Paragraph>
  </Section>
class="xml-element"></Paper>