Developing a tool for creating conceptual and logical models (CLM) based on natural language processing

In data modeling, developing a conceptual model and a logical model is a fundamental design for database systems. Manually developing a conceptual and logical model from the original script requirements requires a lot of time, money and effort. Before using natural language processing techniques, these script requirements must first undergo a few preparatory steps, these steps are crucial because even a minor mistake can have a big impact on the database construction process later on, compared to automated work, manual labor is more prone to errors. In order to create conceptual and logical models, including entity-relationship diagrams (ERDs) and relational database models in a fully automated process from the unconstrained requirements of the initial program text, this research study introduces and develops a (CLM) Tool for creating conceptual and logical models in a fully automated process based on natural language processing(NLP), using a wide range of Heuristic rules and Regular expressions to extract the conceptual and logical model elements more accurately, The ability of a CLM tool to extract models quickly and easily for stakeholders makes it possible for the models to be reviewed and validated multiple times. The overall precision and recall are 0.9351 and 0.9404, respectively, demonstrating the effectiveness of the proposed tool. The (CLM) tool is validated using many case studies and the testing results show that our proposed tool is completely automated and does not necessitate any manual textual processing steps.