On the Limitations of Large Language Models for Conceptual Database Modeling
This article analyzes the use of Large Language Models (LLMs) as support for the conceptual modeling of relational databases through the automatic generation of Entity-Relationship (ER) diagrams from natural language requirements. The approach combines different language models with prompt engineering techniques to evaluate their ability to identify entities, relationships, and attributes in a conceptually consistent manner. The experimental evaluation involved three LLMs, each subjected to three prompting techniques (Zero-Shot, Chain of Thought, and Chain of Thought + Verifier), applied to the same requirements scenario with progressively increasing complexity. The generated diagrams wer...
| Authors | Arthur F. Siqueira, Carlos D. S. Nogueira, Eduarda Farias et al. |
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| Primary category | cs.AI |
| Published | 12 May 2026 |
| Last updated at source | 18 September 2026 |
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