We present a new probabilistic model based on the lexical PCFG model, which can easily utilize the Chinese character information to solve the lexical information sparseness in lexical PCFG model. We discuss in particular some important features that can improve the parsing performance, and describe the strategy of modifying original label structure to reduce the label ambiguities. Final experiment demonstrates that the character information and label modification improve the parsing performance. 