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<Paper uid="P89-1026">
  <Title>HEARER Suzanne ACTION (USE-LANGUAGE AGENT Suzanne LANG is1))) (ASK-ACT AGENT Mrs. de Prado HEARER Suzanne PROP (ABLE-STATE AGENT Suzanne ACTION (USE</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
2. Linguistic Constraints
</SectionTitle>
    <Paragraph position="0"> Speech act interpretation has many similarities to the plan recognition problem. Its goal is, given a situation and an utterance, to understand what the speaker was doing with that utterance, and to find a basis for an appropriate response. In our case this will mean identifying a set of plan structures representing speech acts, which are possible interpretations of the utterance. In this section we show how to use compositional, language-specific rules to provide evidence for a set of partial speech act interpretations, and how to merge them. Later, we use plan reasoning to constrain, supplement, and decide among this set.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
2.1. Notational Aside
</SectionTitle>
      <Paragraph position="0"> Our notation is based on that of \[Allen 87\]. Its essential form is (category &lt;slot filler&gt; &lt;slot filler&gt;...). Categories may be syntactic, semantic, or from the knowledge base. A filler may be a word, a feature, a knowledge-base object (referent) or another (category...) structure.</Paragraph>
      <Paragraph position="1"> Two slots associated with syntactic categories may seem unusual: SEN and RgF. They contain the unit's semantic interpretation, divided into two components. The SEM slot contains a structuralsemantic representation of this instance, based on a small, finite set of thematic roles for verbs and noun phrases. It captures the linguistic generalities of verb subcategorization and noun phrase structure.</Paragraph>
      <Paragraph position="2"> Selectional restrictions, identification of referents, and other phenomena involving world knowledge are captured in the ~ slot. It contains a translation of the SEN slot's logical form into a framelike knowledge representation language, in which richer and more specific role assignments can be made.</Paragraph>
      <Paragraph position="3"> SF.~ thematic roles correspond to different knowledge base roles according to the event class being described, and in REF file corresponding e.v~nt and argument instances are identified ff possio e.</Paragraph>
      <Paragraph position="4"> Distinguishing logical form from knowledge ~p resentafion is an experiment in.tended to clarify e notion of semantic roles in logtcal form, and to reduce the complexity of the interpretation process.</Paragraph>
      <Paragraph position="5"> The senten~ &amp;quot;Can you speak Spanish?&amp;quot; is shown</Paragraph>
    </Section>
  </Section>
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