Relation extraction is an important research in the natural language processing (NLP) area. The constituency grammar information, which is widely believed by the academic community, has an important influence on relation extraction. However, there is no obvious effect when the phrase syntactic tree is applied to the relation extraction task. There are two main reasons for this: First, the generalization ability of the constituency parser is poor, which will cause error propagation and then affect its effectiveness in the relation extraction; Second, there are flaws in the way of the use of the phrase syntactic features in the relation extraction task,that is the phrase syntactic structure information learned by the constituency parser is lost, or the wrong influence on the relation extraction is increased. This paper proposes a Chinese relation extraction method based on constituency vector representation to solve the above two problems. The method embeds the text representation learned by the constituency parser into the relation extraction model, thereby improving the relation extraction performance. This paper validates the method on a public Chinese relation extraction data set.