Joint POS Tagging and Transition-based Constituent Parsing in Chinese with Non-local Features
Zhiguo Wang, Nianwen Xue · 2014
We propose three improvements to ad-dress the drawbacks of state-of-the-art transition-based constituent parsers. First, to resolve the error propagation problem of the traditional pipeline approach, we incorporate POS tagging into the syntac-tic parsing process. Second, to allevi-ate the negative influence of size differ-ences among competing action sequences, we align parser states during beam-search decoding. Third, to enhance the pow-er of parsing models, we enlarge the fea-ture set with non-local features and semi-supervised word cluster features. Exper-imental results show that these modifica-tions improve parsing performance signif-icantly. Evaluated on the Chinese Tree-Bank (CTB), our final performance reach-es 86.3 % (F1) when trained on CTB 5.1, and 87.1 % when trained on CTB 6.0, and these results outperform all state-of-the-art parsers. 1