A Semi-automatic Approach to Identify Business Process Elements in Natural Language Texts

In organizations, business process modeling is very important to report, understand and automate processes. However, the documentation existent in organizations about such processes is mostly unstructured and difficult to be understood by analysts. The extracting of process models from textual descriptions may contribute to minimize the effort required in process modeling. In this context, this paper proposes a semi-automatic approach to identify process elements in natural language texts, which may include process descriptions. Therefore, based on the study of natural language processing, we defined a set of mapping rules to identify process elements in texts. In addition, we developed a prototype which is able to semi-automatically identify process elements in texts. Our evaluation shows promising results. The analyses of 56 texts revealed 91.92% accuracy and a case study showed that 93.33% of the participants agree with the mapping rules.