Is it Harder to Parse Chinese, or the Chinese Treebank?
We present a detailed investigation of the challenges posed when applying parsing models developed against English corpora to Chinese. We develop a factored-model statistical parser for the Penn Chinese Treebank, showing the implications of gross statistical differences between WSJ and Chinese Tree-banks for the most general methods of parser adaptation. We then provide a detailed analysis of the major sources of statistical parse errors for this corpus, showing their causes and relative frequencies, and show that while some types of errors are due to difficult ambiguities inherent in Chinese grammar, others arise due to treebank annotation practices. We show how each type of error can be addressed with simple, targeted changes to the independence assumptions of the maximum likelihood-estimated PCFG factor of the parsing model, which raises our F1 from 80.7% to 82.6% on our development set, and achieves parse accuracy close to the best published figures for Chinese parsing.