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Translation by Structural


Ronald M. Kaplan, Klaus Netter, J?urgen

Wedekind and Annie Zaenen

Abstract. We sketch and illustrate an approach to machine transla-

tion that exploits the potential of simultaneous correspondences between

separate levels of representation, as formalized in the LFG notation of

codescriptions. The approach is illustrated with examples from English,

German and French where the source and the target language sentences

show noteworthy differences in linguistic analyses.

1 Introduction

In this paper we sketch an approach to machine translation that offers

several advantages compared to many of the other strategies currently be-

ing pursued. We define the relationship between the linguistic structures

of the source and target languages in terms of a set of correspondence

functions instead of providing derivational or procedural techniques for

converting source into target. This approach permits the mapping be-

tween source and target to depend on information from various levels of

linguistic abstraction while still preserving the modularity of linguistic

components and of source and target grammars and lexicons. Our con-

ceptual framework depends on notions of structure, structural description,

and structural correspondence. In the following sections we outline these

basic notions and show how they can be used to deal with certain in-

teresting translation problems in a simple and straightforward way. In

This paper originally appeared in Proceedings of the Fourth Conference of the Euro-

pean Chapter of the Association for Computational Linguistics (University of Manch-

ester, 1989), 272{281. Used by permission of the Association for Computational Lin-

guistics; copies of the publication from which this material is derived can can be

obtained through Priscilla Rasmussen, ACL Office Manager, P.O. Box 6090 Somerset,

NJ 08875, USA.

Formal Issues in Lexical-Functional Grammar

edited by

Mary Dalrymple

Ronald M. Kaplan

John T. Maxwell III

Annie Zaenen

Copyright c 1996, Stanford University