The invention discloses a
business process rapid modeling method based on a large
language model. The method comprises the following steps: preprocessing an input
business process description text, and splitting complex sentences and composite sentences into simple sentences by utilizing a large
language model; and extracting the fact types in the simple sentences in a chained manner, wherein the fact types comprise entities, events and event types. And giving a plurality of event relation sets with possible prediction according to the extracted event sets through a large
language model, and combining the event relation sets with the event relation sets extracted in a chain manner to form an event relation
pool. And using the event relationship as a
gene by adopting a
genetic algorithm. After the evolution process of the
genetic algorithm, an event relation set with the highest fitness is filtered out from an event relation
pool. And constructing a
logical relationship between the fact type and the
business process elements, and converting the extracted information into corresponding
json data. The method comprises the following steps of: realizing conversion among structured data through a template, and converting
json data into a
business process execution language (BPEL) and a language for describing a graphic element of a BPMN (
Business Process Execution Language). And finally, inputting the BPEL and a language for describing the BPMN graphic elements into business
flow chart modeling software to generate a visual business
flow chart. Through the above mode, the modeling efficiency can be improved, the modeling threshold can be reduced, and further customization and editing can be carried out in a professional modeling tool to meet specific requirements.