Abstract: The present invention belongs to the technical field of knowledge graph, and provides a knowledge graph construction method for an ethylene oxide derivatives production process. According to data types and characteristics, data sources of the ethylene oxide derivatives production process are sorted and divided into three types: structural data, unstructured data and other types of data. An ontology layer and a data layer of a knowledge graph are constructed by combining top-down and bottom-up methods. A data-driven incremental ontology modeling method is proposed to ensure the expandability of the knowledge graph. For structural knowledge extraction, the safety of original data storage is ensured by means of virtual knowledge graph, and a new mapping mechanism is proposed to realize data materialization. For unstructured knowledge extraction, an entity extraction task is realized on the basis of a BERT-BiLSTM-CRF named entity recognition model by integrating a pre-training language model BERT.