SQL

Natural language to SQL query generation evaluates text-to-query fidelity and schema reasoning. This task is particularly relevant for analytics chat assistants and simplified database interfaces where users need to query data using natural language. Models must understand both the intent behind the question and the structure of the underlying database schema.

Duration

Input Tokens

1002

Output Tokens

1011

Cost

$0.00

Context

Input

Show customer names and the number of service records (as service_count) for their vehicles ordered alphabetically, only customers with service records (not 0)

Expected output

SELECT c.name, COUNT(*) AS service_count FROM customers c JOIN sales s ON c.customer_id = s.customer_id JOIN service_records sr ON s.vehicle_id = sr.vehicle_id GROUP BY c.name ORDER BY c.name;

Model output

SELECT T1.name, COUNT(T3.record_id) AS service_count FROM customers AS T1 INNER JOIN sales AS T2 ON T1.customer_id = T2.customer_id INNER JOIN service_records AS T3 ON T2.vehicle_id = T3.vehicle_id GROUP BY T1.customer_id, T1.name ORDER BY T1.name;