The relations of compound sentences refer to the logical semantic relations between the clauses. The relation recognition of compound sentences is therefore the identification of semantic relations between clauses, and it is a difficult issue in natural language processing (NLP). Taking the marked compound sentences as the research object, this study proposes a BERT-FHAN model. In this model, the BERT model is employed to obtain word vectors, and the HAN model is used to integrate the ontology knowledge of relational words, as well as the characteristics of the part of speech, syntactic dependency relations, and semantic dependency relations. The proposed model is verified by experiments, and the result indicates that the highest macro average F1 value and accuracy of the BERT-FHAN model are 95.47% and 96.97%, respectively, which demonstrates the effectiveness of the method.