Addressing the mismatch between natural language descriptions and the
corresponding SQL queries is a key challenge for text-to-SQL translation. To
bridge this gap, we propose an SQL intermediate representation (IR) called
Natural SQL (NatSQL). Specifically, NatSQL preserves the core functionalities
of SQL, while it simplifies the queries as follows: (1) dispensing with
operators and keywords such as GROUP BY, HAVING, FROM, JOIN ON, which are
usually hard to find counterparts for in the text descriptions; (2) removing
the need for nested subqueries and set operators; and (3) making schema linking
easier by reducing the required number of schema items. On Spider, a
challenging text-to-SQL benchmark that contains complex and nested SQL queries,
we demonstrate that NatSQL outperforms other IRs, and significantly improves
the performance of several previous SOTA models. Furthermore, for existing
models that do not support executable SQL generation, NatSQL easily enables
them to generate executable SQL queries, and achieves the new state-of-the-art
execution accuracy.

提出一种名为自然 SQL（NatSQL）的 SQL 中间表示，通过去除难以在文本中找到对应词的运算符和关键字、消除嵌套子查询和 set 运算符的需要，以及降低必要模式项的数量来简化查询，从而提高了现有模型的性能，并使得不支持可执行 SQL 生成的模型能够生成可执行的 SQL 查询，并实现了新的最新执行准确度。