The emergency plan of the urban rail transit (URT) system is a guiding document for dealing with emergencies and formulating emergency plans. However, the emergency plan text described in natural language has some problems, such as poor visibility and enforceability. Effective help is difficult to provide for the rapid implementation of emergency response. Therefore, obtaining key emergency task information from the emergency response plan and visualizing the emergency disposal workflow are the main challenges. In this article, we propose a method of extracting emergency elements (EELs) from emergency plans and constructing a business process model. First, a nested entity extraction model incorporating adversarial training is proposed to extract EELs from the complex sentences in the emergency plan text. Second, the EELs are combined into emergency task units, and then the relations between emergency task units are identified to form the emergency task sequence flow, which is stored in matrix form. Finally, the emergency disposal workflow model is generated based on the emergency task sequence flow and the BPMN modeling method. Taking the actual emergency plan text as an example, the process from the extraction of EELs to the construction of the disposal workflow model is demonstrated. Experimental results prove that this method has advantages in comprehensively extracting EELs, visualizing the emergency disposal workflow, and improving the enforceability of emergency plans.