Paper: Experiments with a Higher-Order Projective Dependency Parser

ACL ID D07-1101
Title Experiments with a Higher-Order Projective Dependency Parser
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

We present experiments with a dependency parsing model defined on rich factors. Our model represents dependency trees with fac- tors that include three types of relations be- tween the tokens of a dependency and their children. We extend the projective pars- ing algorithm of Eisner (1996) for our case, and train models using the averaged percep- tron. Our experiments show that consider- ing higher-order information yields signifi- cant improvements in parsing accuracy, but comes at a high cost in terms of both time and memory consumption. In the multi- lingual exercise of the CoNLL-2007 shared task (Nivre et al. , 2007), our system obtains the best accuracy for English, and the second best accuracies for Basque and Czech.