Discipline construction is the core of the development of colleges and universities. With the deepening and strengthening of discipline construction in colleges and universities, the information on discipline construction increases continuously. Nevertheless, the results of discipline construction can not be effectively managed in the manner of discrete document organization, which is not conducive to subsequent analysis and evaluation. To solve this problem, this study focuses on the construction and further application of discipline construction-oriented knowledge graphs. For this purpose, events are extracted from discipline construction texts by the BERT-BiLSTM-CRF model, and related knowledge is supplemented by the crawler. Then, the property graph model is selected to store knowledge, and a preliminary discipline construction-oriented knowledge graph is thereby built. Subsequently, this knowledge graph is availed to build a visualization system for discipline construction, and the minimum Steiner tree algorithm is adopted for the application of intelligent question answering. Finally, the validity of the proposed method is verified by experimental analysis of the methods of discipline construction-oriented event extraction and intelligent question answering.