| Dependency Parsing: Baseline | In detail, a shift-reduce method is adopted as in (Nivre, 2003), where a classifier is used to make a parsing decision step by step. |
| Dependency Parsing: Baseline | While memory-based and margin-based learning approaches such as support vector machines are popularly applied to shift-reduce parsing, we apply maximum entropy model as the learning model for efficient training and adopting overlapped features as our work in (Zhao and Kit, 2008), especially, those character-level ones for Chinese parsing. |
| Dependency Parsing: Baseline | Without this type of features, a shift-reduce parser may directly scan through an input sequence in linear time. |
| Evaluation Results | beam search algorithm with width 5 is used for parsing, otherwise, a simple shift-reduce decoding is used. |