Probabilistic Models for High-Order Projective Dependency Parsing
Table 5: Accuracy comparisons of different dependency parsers on PTB, CTB and PDT.
['[EMPTY]', '[BOLD] Eng UAS', '[BOLD] Eng CM', '[BOLD] Chn UAS', '[BOLD] Chn CM', '[BOLD] Cze UAS', '[BOLD] Cze CM']
Our experimental results show an improvement in performance of English and Chinese over the results in Zhang and Clark \shortcitezhang:2008, which combining graph-based and transition-based dependency parsing into a single parser using the framework of beam-search, and Zhang and Nivre \shortcitezhang:ACL11, which are based on a transition-based dependency parser with rich non-local features. For English and Czech, our results are better than the results of the two third-order graph-based dependency parsers in Koo and Collins \shortciteKoo:2010. The models marked * cannot be compared with our work directly, as they exploit large amount of additional information that is not used in our models, whiling our parses obtain results competitive with these works. For example, Koo et al. \shortciteKoo-dp:2008 and Suzuki et al. \shortciteSuzuki:2009 make use of unlabeled data, and the parsing model of Zhang and Clark \shortcitezhang:2009 utilizes phrase structure annotations.