Attribute Grammars: a Declarative Functional Language

Projet CHARMEAlthough Attribute Grammars were introduced thirty years ago, their lack of expressiveness has resulted in limited use outside the domain of static language processing. In this paper we show that it is possible to extend this expressiveness. We claim that Attribute Grammars can be used to describe computations on structures that are not just trees, but also on abstractions allowing for infinite structures. To gain this expressiveness, we introduce two new notions: {\em scheme productions\/} and {\em conditional productions}. The result is a language that is comparable in power to most first-order functional languages, with a distinctive declarative character. Our extensions deal with a different part of the Attribute Grammars formalism than what is used in most works on Attribute Grammars including global analysis and evaluator generation. Hence, most existing results are directly applicable to our extended Attribute Grammars including efficient implementation (in our case, using the FNC-2 system http://www-rocq.inria.fr/charme/FNC-2/). The major contribution of this approach is to restore and re-emphasize the intrinsic power of Attribute Grammars. Furthermore, our extensions call for new studies on applying to functional programming the analysis and implementation techniques developed for Attribute Grammars

Treebank-based acquisition of wide-coverage, probabilistic LFG resources: project overview, results and evaluation

This paper presents an overview of a project to acquire wide-coverage, probabilistic Lexical-Functional Grammar (LFG) resources from treebanks. Our approach is based on an automatic annotation algorithm that annotates “raw” treebank trees with LFG f-structure information approximating to basic predicate-argument/dependency structure. From the f-structure-annotated treebank we extract probabilistic unification grammar resources. We present the annotation algorithm, the extraction of lexical information and the acquisition of wide-coverage and robust PCFG-based LFG approximations including long-distance dependency resolution. We show how the methodology can be applied to multilingual, treebank-based unification grammar acquisition. Finally we show how simple (quasi-)logical forms can be derived automatically from the f-structures generated for the treebank trees