Exploring Temporal Text-to-SQL Challenges in Brazilian Portuguese: Lessons from Educational Data - Fróes, Karina de Carvalho; Braghetto, Kelly Rosa (Anais do Simpósio Brasileiro de Banco de Dados (SBBD); 2025: Anais do XL Simpósio Brasileiro de Bancos de Dados, 2025)
Recent advances in natural language processing have enabled translating natural language into SQL, but challenges remain in multilingual and temporal contexts. This short paper presents a beginner-level exploratory analysis of a prompt engineering strategy for text-to-SQL generation over Brazilian Portuguese educational data. Through 10 representative examples reflecting how real users might ask questions about open government data, we show how language variability, implicit temporal references, and mismatched expectations affect SQL generation and the reliability of standard evaluation metrics. This work contributes to historical data querying research and highlights persistent challenges for multilingual text-to-SQL systems.