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<Paper uid="C04-1189">
  <Title>HITIQA: Towards Analytical Question Answering</Title>
  <Section position="3" start_page="2" end_page="2" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> Our objective in HITIQA is to allow the user to submit exploratory, analytical questions, such as &amp;quot;What has been Russia's reaction to the U.S.</Paragraph>
    <Paragraph position="1"> bombing of Kosovo?&amp;quot; The distinguishing property of such questions is that one cannot generally anticipate what might constitute the answer. While certain types of things may be expected (e.g., diplomatic statements), the answer is heavily conditioned by what information is in fact available on the topic. From a practical viewpoint, analytical questions are often underspecified, thus casting a broad net on a space of possible answers.</Paragraph>
    <Paragraph position="2"> Questions posed by professional analysts are aimed to probe the available data along certain dimensions. The results of these probes determine follow up questions, if necessary. Furthermore, at any stage clarifications may be needed to adjust the scope and intent of each question. Figure 1 shows a fragment of an analytical session with HITIQA; note that these questions are not aimed at factoids, despite their simple form.</Paragraph>
    <Paragraph position="3"> User: What is the history of the nuclear arms program linking Iraq and other countries in the region? HITIQA: [responses and clarifications] User: Who financed the nuclear arms program in Iraq? HITIQA:...</Paragraph>
    <Paragraph position="4"> User: Has Iraq been able to import uranium? HITIQA:...</Paragraph>
    <Paragraph position="5"> User: What type of debt does exist between Iraq and her trading partners in the region?  FIGURE 1: A fragment of an analyst's session with HITIQA HITIQA project is part of the ARDA AQUAINT program that aims to make significant advances in the state of the art of automated question answering. In this paper we focus on three aspects of our work: 1. Question Semantics: how the system &amp;quot;understands&amp;quot; user requests 2. Human-Computer Dialogue: how the user and the system negotiate this understanding 3. User Evaluations and Results 2 Factoid vs. Analytical QA  There are significant differences between factoid, or fact-finding, and analytical question answering. A factoid question is normally understood to seek a piece of information that would make a corresponding statement true (i.e., it becomes a fact): &amp;quot;How many states are in the U.S.?&amp;quot; / &amp;quot;There are X states in the U.S.&amp;quot; In this sense, a factoid question usually has just one correct answer that can generally be judged for its truthfulness with respect to some information source.</Paragraph>
    <Paragraph position="6"> As noted by Harabagiu et al. (1999), factoid questions display a distinctive &amp;quot;answer type&amp;quot;, which is the type of the information item needed for the answer, e.g., &amp;quot;person&amp;quot; or &amp;quot;country&amp;quot;, etc. Most existing factoid QA systems deduct this expected answer type from the form of the question using a finite list of possible answer types. For example, &amp;quot;Who was the first man in space&amp;quot; expects a &amp;quot;person&amp;quot; as the answer type. This is generally a very good strategy that has been exploited successfully in a number of automated QA systems, especially in the context of TREC</Paragraph>
  </Section>
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