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<Paper uid="P01-1028">
  <Title>Generating with a Grammar Based on Tree Descriptions: a Constraint-Based Approach</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> We take the axiomatic view of language and show that it yields an interestingly new perspective on the tactical generation task i.e. the task of producing from a given semantics a0 a string with semantics a0 .</Paragraph>
    <Paragraph position="1"> As (Cornell and Rogers, To appear) clearly shows, there has recently been a surge of interest in logic based grammars for natural language. In this branch of research sometimes referred to as &amp;quot;Model Theoretic Syntax&amp;quot;, a grammar is viewed as a set of axioms defining the well-formed structures of natural language.</Paragraph>
    <Paragraph position="2"> The motivation for model theoretic grammars is initially theoretical: the use of logic should support both a more precise formulation of grammars and a different perspective on the mathematical and computational properties of natural language.</Paragraph>
    <Paragraph position="3"> But eventually the question must also be addressed of how such grammars could be put to work. One obvious answer is to use a model generator. Given a logical formula a0 , a model generator is a program which builds some of the models satisfying this formula. Thus for parsing, a model generator can be used to enumerate the (minimal) model(s), that is, the parse trees, satisfying the conjunction of the lexical categories selected on the basis of the input string plus any additional constraints which might be encoded in the grammar. And similarly for generation, a model generator can be used to enumerate the models satisfying the bag of lexical items selected by the lexical look up phase on the basis of the input semantics.</Paragraph>
    <Paragraph position="4"> How can we design model generators which work efficiently on natural language input i.e. on the type of information delivered by logic based grammars? (Duchier and Gardent, 1999) shows that constraint programming can be used to implement a model generator for tree logic (Backofen et al., 1995). Further, (Duchier and Thater, 1999) shows that this model generator can be used to parse with descriptions based grammars (Rambow et al., 1995; Kallmeyer, 1999) that is, on logic based grammars where lexical entries are descriptions of trees expressed in some tree logic.</Paragraph>
    <Paragraph position="5"> In this paper, we build on (Duchier and Thater, 1999) and show that modulo some minor modifications, the same model generator can be used to generate with description based grammars.</Paragraph>
    <Paragraph position="6"> We describe the workings of the algorithm and compare it with standard existing top-down and bottom-up generation algorithms. In specific, we argue that the change of perspective offered by the constraint-based, axiomatic approach to processing presents some interesting differences with the more traditional generative approach usually pursued in tactical generation and further, that the combination of this static view with a TAG-like grammar and a flat semantics results in a system which combines the positive aspects of both top-down and bottom-up generators.</Paragraph>
    <Paragraph position="7"> The paper is structured as follows. Section 2 presents the grammars we are working with namely, Description Grammars (DG), Section 3 summarises the parsing model presented in (Duchier and Thater, 1999) and Section 4 shows that this model can be extended to generate with DGs. In Section 5, we compare our generator with top-down and bottom-up generators, Section 6 reports on a proof-of-concept implementation and Section 7 concludes with pointers for further research.</Paragraph>
  </Section>
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