Parsing Chinese with head-driven model

Great progress has been made in parsing the Wall Street Journal portion of the Penn Treebank. Now parsing languages other than English is an intensive research area. Head-driven model is one of the best English parsing models. It has been successfully applied to Czech but failed to outperform a base-line model in parsing German. This paper attempts to parse Chinese with head-driven model. Promising experimental results demonstrate that head-driven model works well for Chinese. We propose a hybrid parsing strategy, which combines head-driven model with a Chinese base phrases parsing model. The combined model not only improves the performance but also makes the parser space and time efficient. We evaluate our method in PARSEVAL measures, and the combined model performances are at 79.88% precision, 81.97% recall.