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<Paper uid="P06-1135">
  <Title>Improving QA Accuracy by Question Inversion</Title>
  <Section position="4" start_page="1073" end_page="1073" type="intro">
    <SectionTitle>
2 Related Work
</SectionTitle>
    <Paragraph position="0"> Logic and inferencing have been a part of Question-Answering since its earliest days. The first such systems were natural-language interfaces to expert systems, e.g., SHRDLU (Winograd, 1972), or to databases, e.g., LIFER/LADDER (Hendrix et al.</Paragraph>
    <Paragraph position="1"> 1977). CHAT-80 (Warren &amp; Pereira, 1982), for instance, was a DCG-based NL-query system about world geography, entirely in Prolog. In these systems, the NL question is transformed into a semantic form, which is then processed further. Their overall architecture and system operation is very different from today's systems, however, primarily in that there was no text corpus to process.</Paragraph>
    <Paragraph position="2"> Inferencing is a core requirement of systems that participate in the current PASCAL Recognizing Textual Entailment (RTE) challenge (see http://www.pascal-network.org/Challenges/RTE and .../RTE2). It is also used in at least two of the more visible end-to-end QA systems of the present day.</Paragraph>
    <Paragraph position="3"> The LCC system (Moldovan &amp; Rus, 2001) uses a Logic Prover to establish the connection between a candidate answer passage and the question. Text terms are converted to logical forms, and the question is treated as a goal which is &amp;quot;proven&amp;quot;, with real-world knowledge being provided by Extended WordNet. The IBM system PIQUANT (Chu-Carroll et al., 2003) used Cyc (Lenat, 1995) in answer verification. Cyc can in some cases confirm or reject candidate answers based on its own store of instance information; in other cases, primarily of a numerical nature, Cyc can confirm whether candidates are within a reasonable range established for their subtype.</Paragraph>
    <Paragraph position="4"> At a more abstract level, the use of inversions discussed in this paper can be viewed as simply an example of finding support (or lack of it) for candidate answers. Many current systems (see, e.g. (Clarke et al., 2001; Prager et al. 2004b)) employ redundancy as a significant feature of operation: if the same answer appears multiple times in an internal top-n list, whether from multiple sources or multiple algorithms/agents, it is given a confidence boost, which will affect whether and how it gets returned to the end-user.</Paragraph>
    <Paragraph position="5"> The work here is a continuation of previous work described in (Prager et al. 2004a,b). In the former we demonstrated that for a certain kind of question, if the inverted question were given, we could improve the F-measure of accuracy on a question set by 75%. In this paper, by contrast, we do not manually provide the inverted question, and in the second evaluation presented here we do not restrict the question type.</Paragraph>
  </Section>
class="xml-element"></Paper>