The invention relates to an evaluation object extraction method based on a domain dictionary and semantic roles and belongs to the field of natural language processing application technologies. The evaluation object extraction method based on the domain dictionary and the semantic role comprises the following steps that firstly, according to the information of the part of speech, dependency information and semantic role information, the domain dictionary DL of evaluation objects is established; secondly, the characteristics in the four aspects of words, dependency, relative positions and the semantic roles are fully extracted, model training and prediction are carried out on the DL and the characteristics through conditional random fields (CRFs), and then the extraction of the evaluation objects is completed. Compared with the prior art, according to the characteristics that the structures of Chinese sentences, especially Chinese sentences of microblogs and forum evaluation information are flexible and diverse, the constructive methods are variable, and the number of the characteristics of the sentences is small, the syntax of different levels and the semantic information are fully utilized, the advantages of the evaluation object extraction method based on rules and machine learning are also utilized, the evaluation object with a high confidence coefficient is found from a corpus automatically, rapidly and accurately, and the accuracy of extraction of the evaluation objects of the Chinese sentences is improved.