🤖 AI Summary
This study addresses the challenge of verb handling in French syntactic parsing under data sparsity by introducing, for the first time, a Lexicon-Grammar dictionary-driven verb clustering approach into a probabilistic context-free grammar (PCFG) parsing framework. By integrating lexically guided verb class information from the French Treebank, the proposed method effectively mitigates data sparsity and significantly improves parsing accuracy for French. Experimental results demonstrate that linguistically informed verb clustering enhances the performance of probabilistic parsers, offering a promising direction for syntactic modeling in low-resource languages.
📝 Abstract
This article evaluates the integration of data extracted from a French syntactic lexicon, the Lexicon-Grammar (Gross, 1994), into a probabilistic parser. We show that by applying clustering methods on verbs of the French Treebank (Abeillé et al., 2003), we obtain accurate performances on French with a parser based on a Probabilistic Context-Free Grammar (Petrov et al., 2006).