This work introduces semantic captioning for SQL queries, addressing the reverse operation of semantic parsing by translating SQL code into natural language explanations. Using graph-aware few-shot in-context learning with smaller LLMs, our approach outperforms random selection by up to 39% on BLEU score, providing crucial capabilities for understanding and explaining LLM-generated SQL code in security-critical applications.
