<?xml version="1.0" standalone="yes"?>
<Paper uid="W04-2502">
  <Title>Answering Questions Using Advanced Semantics and Probabilistic Inference</Title>
  <Section position="8" start_page="0" end_page="0" type="concl">
    <SectionTitle>
5 Conclusions
</SectionTitle>
    <Paragraph position="0"> In this paper we show that, while there has been much progress in natural language analysis there is still a large gap in representing knowledge and reasoning with it for advanced QA. We have developed a method for processing complex questions which involves the identification of several forms of complex semantic structures. This involves the development of a powerful semantic grammar formalism - Embodied Construction Grammar (ECG) and applying it to the analysis of complex questions. Answer Extraction will be performed by recognizing event inter-relationships, recognized by novel relation extraction techniques. Question extraction at the level the AQUAINT program seeks requires a mechanism for performing inference over multiple sentences and texts, using background knowledge. We propose to build a software package which we refer to as Probabilistic Inference Networks (PIN) to provide a mechanism for performing context-sensitive inference over multiple sentences and discourse fragments, using encoded knowledge.</Paragraph>
  </Section>
class="xml-element"></Paper>