Natural Language–Based Conceptual Modelling Frameworks: State of the Art and Future Opportunities

• Published in: ACM computing surveys Vol. 56; no. 1; pp. 1 - 26
• Main Authors: Hossain, Bayzid Ashik, Mukta, Md. Saddam Hossain, Islam, Md Adnanul, Zaman, Akib, Schwitter, Rolf
• Format: Journal Article
• Language: English
• Published: New York, NY ACM 31.01.2024; Association for Computing Machinery
• Subjects: Computer science; Engineers; General and reference; Information systems; Knowledge; Knowledge representation; Language; Logic; Modelling; Natural language; Natural language processing; Relational database model; Requirements analysis; Requirements specifications; Software and its engineering; Software engineering; State of the art; Subject specialists; Surveys and overviews; Systems design; Theory of computation; conceptual modelling; information extraction; Natural language processing; semantic round-tripping; knowledge representation
• ISSN: 0360-0300; 1557-7341
• DOI: 10.1145/3596597

Identifying requirements for an information system is an important task and conceptual modelling is the first step in this process. Conceptual modelling plays a critical role in the information system design process and usually involves domain experts and knowledge engineers who brainstorm together to identify the required knowledge to build an information system. The conceptual modelling process starts with the collection of necessary information from the domain experts by the knowledge engineers. Afterwards, the knowledge engineers use traditional model driven engineering techniques to design the system based on the collected information. Natural language–based conceptual modelling frameworks or systems are used to help domain experts and knowledge engineers in eliciting requirements and building conceptual models from a natural language text. In this article, we discuss the state of the art of some recent conceptual modelling frameworks that are based on natural language. We take a closer look at how these frameworks are built, in particular at the underlying motivation, architecture, types of natural language used (e.g., restricted vs. unrestricted), types of the conceptual model generated, verification support of the requirements specifications as well as the conceptual models, and underlying knowledge representation formalism. We also discuss some future research opportunities that these frameworks offer.