The invention discloses an enterprise entity relation extraction method based on a convolutional neural network. The method comprises the steps of a relation corpus building stage, wherein an initial seed relation pair set is built artificially, and by means of an internet search engine and a Bootstrapping technology, relation language materials are generated in an iteration mode, and finally a relation corpus is formed; a relation classification model training stage, wherein term vectors and position embedding are combined to build a sentence vector matrix representation to serve as input of a network, the convolutional neural network is built, the network is trained by means of a back propagation algorithm, and a relation classification model is obtained; an enterprise entity relation extraction stage in a web page, wherein the web page is preprocessed by combining web page text extraction with a named entity identification technology, and then enterprise entity relation extraction is conducted on the preprocessed web page. By means of the method, not only the defects of an artificial feature method can be overcome, but also the enterprise entity relation can be extracted from the web page more accurately and efficiently.