Online Large-Margin Training of Dependency Parsers

著者: Ryan T. McDonald, Koby Crammer, Fernando C. N. Pereira - Annual Meeting of the Association for Computational Linguistics, ACL 2005 被引用: 816

We present an effective training algorithm for linearly-scored dependency parsers that implements online large-margin multi-class training (Crammer and Singer, 2003; Crammer et al., 2003) on top of efficient parsing techniques for dependency trees (Eisner, 1996). The trained parsers achieve a competitive dependency accuracy for both English and Czech with no language specific enhancements.