Generating with a Grammar Based on Tree Descriptions: a Constraint-Based Approach

Generating with a Grammar Based on Tree Descriptions: a Constraint-Based Approach Claire Gardent CNRS LORIA, BP 239 Campus Scientifique 54506 Vandoeuvre-les-Nancy, France claire.gardent@loria.fr Stefan Thater Computational Linguistics Universit¨at des Saarlandes Saarbr¨ucken, Germany stth@coli.uni-sb.de Abstract While the generative view of language processing builds bigger units out of smaller ones by means of rewriting steps, the axiomatic view eliminates in- valid linguistic structures out of a set of possible structures by means of well- formedness principles. We present a generator based on the axiomatic view and argue that when combined with a TAG-like grammar and a flat seman- tics, this axiomatic view permits avoid- ing drawbacks known to hold either of top-down or of bottom-up generators. 1 Introduction 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 produc- ing from a given semantics � a string with seman- tics � . 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 “Model Theoretic Syntax”, a grammar is viewed as a set of axioms defining the well-formed struc- tures of natural language. The motivation for model theoretic grammars is initially theoretical: the use of logic should sup- port both a more precise formulation of grammars and a different perspective on the mathematical and computational properties of natural language. But eventually the question must also be ad- dressed of how such grammars could be put to work. One obvious answer is to use a model gen- erator. Given a logical formula � , a model genera- tor 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 gram- mar. And similarly for generation, a model gener- ator can be used to enumerate the models satisfy- ing the bag of lexical items selected by the lexical look up phase on the basis of the input semantics. 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 im- plement a model generator for tree logic (Back- ofen et al., 1995). Further, (Duchier and Thater, 1999) shows that this model generator can be used to parse with descriptions based grammars (Ram- bow et al., 1995; Kallmeyer, 1999) that is, on logic based grammars where lexical entries are descriptions of trees expressed in some tree logic. In this paper, we build on (Duchier and Thater, 1999) and show that modulo some minor modi- fications, the same model generator can be used to generate with description based grammars. We …

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