Efficient Parsing for French

EFFICIENT PARSING FOR FRENCH* Claire Gardent University Blaise Pascal - Clermont II and University of Edinburgh, Centre for Cognitive Science, 2 Buccleuch Place, Edinburgh EH89LW, SCOTLAND, LrK Gabriel G. B~s, Pierre-Franqois Jude and Karine Baschung, Universit~ Blaise Pascal - Clermont II, Formation Doctorale Linguistique et Informatique, 34, Ave, Carnot, 63037 Clermont-Ferrand Cedex, FRANCE ABSTRACT Parsing with categorial grammars often leads to problems such as proliferating lexical ambiguity, spu- rious parses and overgeneration. This paper presents a parser for French developed on an unification based categorial grammar (FG) which avoids these pro- blem s. This parser is a bottom-up c hart parser augmen- ted with a heuristic eliminating spurious parses. The unicity and completeness of parsing are proved. INTRODUCTION Our aim is twofold. First to provide a linguistical- ly well motivated categorial grammar for French (henceforth, FG) which accounts for word order varia- tions without overgenerating and without unnecessary lexical ambiguities. Second, to enhance parsing effi- ciency by eliminating spurious parses, i.e. parses with • different derivation trees but equivalent semantics. The two goals are related in that the parsing strategy relies on properties of the grammar which are indepen- dently motivated by the linguistic data. Nevertheless, the knowledge embodied in the grammar is kept inde- pendent from the processing phase. 1. LINGUISTIC THEORIES AND WORD ORDER Word order remains a pervasive issue for most linguistic analyses. Among the theories most closely related to FG, Unification Categorial Grammar (UCG : Zeevat et al. 1987), Combinatory Categorial Grammar (CCG : Steedman 1985, Steedman 1988), Categorial Unification Grammar (CUG : Karttunen 1986) and Head-driven Phrase Structure Grammar (I-IPSG: Pollard & Sag 1988) all present inconvenien- ces in their way of dealing with word order as regards parsing efficiency and/or linguistic data. * The workreported here was carried outin the ESPR/T Project 393 ACORD, ,,The Construction and Interrogation of Knowledge Bases using Natural Language Text and Graphics~. 280 In UCG and in CCG, the verb typically encodes the notion of a canonical ordering of the verb arguments. Word order variations are then handled by resorting to lexical ambiguity and jump rules ~ (UCG) or to new combinators (CCG). As a result, the number of lexical and/or phrasal edges increases rapidly thus affecting parsing efficiency. Moreover, empirical evidence does not support the notion of a canonical order for French (cf. B~s & Gardent 1989). In contrast, CUG, GPSG (Gazdar et al. 1985) and HPSG do not assume any canonical order and subcate- gorisation information is dissociated from surface word order. Constraints on word order are enforced by features and graph unification (CUG) or by Linear Pre- cedence (LP) statements (HPSG, GPSG). The pro- blems with CUG are that on the computational side, graph-unification is costly and less efficient in a Prolog environment than term unification while from the linguistic point of view (a) NP's must be assumed unambiguous with respect to case which is not true for - at least - French and (b) clitic doubling cannot be ac- counted for as a result of …

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