Corpus-Based Grammar Specialization

In: Proceedings of CoNLL-2000 and LLL-2000, pages 7-12, Lisbon, Portugal, 2000. Corpus-Based Grammar Specialization Nicola Cancedda and Christer Samuelsson Xerox Research Centre Europe 6, chemin de Maupertuis 38240, Meylan, France {Nicola. Cancedda, Christer. Samuelsson}@xrce. xerox, com Abstract Broad-coverage grammars tend to be highly am- biguous. When such grammars are used in a restricted domain, it may be desirable to spe- cialize them, in effect trading some coverage for a reduction in ambiguity. Grammar specializa- tion is here given a novel formulation as an opti- mization problem, in which the search is guided by a global measure combining coverage, ambi- guity and grammar size. The method, applica- ble to any unification grammar with a phrase- structure backbone, is shown to be effective in specializing a broad-coverage LFG for French. 1 Introduction Expressive grammar formalisms allow grammar developers to capture complex linguistic gener- alizations concisely and elegantly, thus greatly facilitating grammar development and main- tenance. Broad-coverage grammars, however, tend to overgenerate considerably, thus allowing large amounts of spurious ambiguity. If the ben- efits resulting from more concise grammatical descriptions are to outweigh the costs of spuri- ous ambiguity, the latter must be brought down. We here investigate a corpus-based compilation technique that reduces overgeneration and spu- rious ambiguity without jeopardizing coverage or burdening the grammar developer. The current work extends previous work on corpus-based grammar specialization, which applies variants of explanation-based learning (EBL) to grammars of natural languages. The earliest work (Rayner, 1988; Samuelsson and Rayner, 1991) builds a specialized grammar by chunking together grammar rule combinations while parsing training examples. What rules to combine is specified by hand-coded criteria. Subsequent work (Rayner and Carter, 1996; Samuelsson, 1994) views the problem as that of cutting up each tree in a treebank of cor- rect parse trees into subtrees, after which the rule combinations corresponding to the subtrees determine the rules of the specialized gram- mar. This approach reports experimental re- sults, using the SRI Core Language Engine, (Alshawi, 1992), in the ATIS domain, of more than a 3-fold speedup at a cost of 5% in gram- matical coverage, the latter which is compen- sated by an increase in parsing accuracy. Later work (Samuelsson, 1994; Sima'an, 1999) at- tempts to automatically determine appropriate tree-cutting criteria, the former using local mea- sures, the latter using global ones. The current work reverts to the view of EBL as chunking grammar rules. It extends the latter work by formulating grammar special- ization as a global optimization problem over the space of all possible specialized grammars with an objective function based on the cover- age, ambiguity and size of the resulting gram- mar. The method was evaluated on the LFG grammar for French developed within the PAR- GRAM project (Butt et al., 1999), but it is applicable to any unification grammar with a phrase-structure backbone where the reference treebank contains all possible analyses for each training example, along with an indication of which one is the correct one. To explore the space of possible grammars, a special …

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