A Concept for Integrating an LLM-Based Natural Language Interface for Visualizations Grammars

In this paper, we propose a natural language interface visualization framework leveraging visualization grammar to balance the flexibility and stability of generated visualizations. Our system employs a JSON schema for visualization specification and an instruction prompt with semantically distinct sections for task context, visualizations, datasets, and control mechanisms. This design enables robust state management, live prompt adjustments, ensures clarity, consistency, and reusability in visualization generation.