<?xml version="1.0" standalone="yes"?>
<Paper uid="C00-2155">
  <Title>An HPSG-to-CFG Approximation of Japanese</Title>
  <Section position="3" start_page="0" end_page="1046" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> This paper presents a simple approximation method for turning an HPSG (Pollard and Sag, 1994) into a context-free grmnmar. The theoretical underpinning is established through a least fixpoint construction over a certain monotonic function, similar to the instantiation of a rule in a bottom-up passive chart parser or to partial evaluation in logic programming; see (Kiefer and Krieger, 2000a).</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
1.1 Basic Idea
</SectionTitle>
      <Paragraph position="0"> The intuitive idea underlying our approach is to generalize in a first step the set of all lexicon entries. The resulting structures form equivalence classes, since they abstract from word-specific information, such as FORN or STEM. The abstraction is specified by means of a restrictor (Shiet)er, 1985), the so-called lexicon rcstrictor.</Paragraph>
      <Paragraph position="1"> The grammar rules/schemata are then instantiated via unification, using the abstracted lexicon entries, yielding derivation trees of depth 1.</Paragraph>
      <Paragraph position="2"> We apply the rule restrictor to each resulting feature structure, which removes all information contained only in the daughters of the rule. Due to the Locality Principle of HPSG, this deletion does not alter the set of derivable feature structures. Since we are interested in a finite fixpoint from a practical point of view, the restriction also gets rid of information that will lead to infinite growth of feature structures during derivation. Additionally, we throw away information that will not restrict the search space (typically, parts of tile semantics). The restricted feature structures (together with older ones) then serve as tile basis for the next instantiation step.</Paragraph>
      <Paragraph position="3"> Again, this gives us feature structures encoding a derivation, and again we are applying the rule restrictor. We proceed with the iteration, until we reach a fixpoint, meaning that further iteration steps will not add (or remove) new (o1&amp;quot; old) feature structures.</Paragraph>
      <Paragraph position="4"> Our goal, however, is to obtain a context-fl'ee grammar, trot since we have reached a fixpoint, we can use the entire feature structures as (complex) context-free symbols (e.g., by nlapping them to integers). By instantiating the HPSG rules a final time with feature structures from the fixpoint, applying the rule restrictor and finally classifying the resulting structure (i.e., find tile right structure from the fixpoint), one can easily obtain tile desired context-free grainmar (CFG).</Paragraph>
    </Section>
    <Section position="2" start_page="0" end_page="1046" type="sub_section">
      <SectionTitle>
1.2 Why is it Worth?
</SectionTitle>
      <Paragraph position="0"> Approximating an HPSG through a CFG ~ is interesting for the following practical reason: assuming that we have a CFG that comes close to an HPSG, we can use the CFG as a cheap filter (running time complexity is O(IGI 2 x n 3) for an arbitrary sentence of length n). The main idea is to use the CFG first and then let the HPSG deterministically replay the derivations licensed by the CFG. The important point here is that one can find for every CF production exactly one and only one HPSG rule. (Kasper et al., 1996) describe such an approach for word graph parsing which employs only the relatively unspecific CF backbone of an HPSG-like grmnmar. (Diagne et al., 1995) replaces the CF backbone through a restriction of the original HPSG. This grammar, however, is still an unification- null based grammar, since it employs coreference constraints.</Paragraph>
      <Paragraph position="1"> 1..3 Content of Paper In tile next section, we describe the Japanese HPSG that is used in Verbmobil, a project that deals with the translation of spontaneously spoken dialogues between English, German, and Japanese speakers. After that, section 3 explains a simplified, albeit correct version of the implemented algorithm. Section 4 then discusses the outcome of the approximation process. null</Paragraph>
    </Section>
  </Section>
class="xml-element"></Paper>