Neural Character-level Dependency Parsing for Chinese

This inconvenience makes us do necessary restorations from character-level dependency parsing results Table 2: Character-level evaluation. Character-level dependency parsing covers all levels of language processing within a Chinese sentence. Our model shows that even integrating the least character position simplifies the pipeline into two steps, character POS tagging, information, it is beneficial to the parser.. and character dependency parsing, while traditional processing Finally, effective integration of two levels of tags boosts has to handle word segmentation, POS tagging for word, the performance most. For CHAR WORD strategy, it is more and word-level dependency parsing as shown in Figure 2. straightforward but also brings too many tags or labels and With different processing hierarchies, we also provide complete thus will slow down the parsing and make the learning more matches (CM) as one metric for the related evaluation. The character parsing performance comparison is given in Table reason might be that since characters instead of words are 1, in which the following observations are obtained.