Dial: A Knowledge-Grounded Dialect-Specific NL2SQL System

Abstract:Enterprises commonly deploy heterogeneous database systems, each of which owns a distinct SQL dialect with different syntax rules, built-in functions, and execution constraints. However, most existing NL2SQL methods assume a single canonical dialect (e.g., SQLite) and struggle to produce queries that are both semantically correct and executable on target engines. Prompt-based approaches tightly couple intent reasoning with dialect syntax, rule-based translators often degrade native operators into generic constructs, and multi-dialect fine-tuning suffers from cross-dialect interference. In this paper, we present Dial, a knowledge-grounded framework for dialect-specific NL2SQL. Dial introduces: (1) a Dialect-Aware Logical Query Planning module that converts natural language into a dialect-aware logical query plan via operator-level intent decomposition and divergence-aware specification; (2) HINT-KB, a hierarchical intent-aware knowledge base that organizes dialect knowledge into i a Canonical Syntax Reference, ii a declarative function repository, and iii a procedural constraint repository; and (3) an execution-driven debugging and semantic verification loop that separates syntactic recovery from logic auditing to prevent semantic drift. We construct DS-NL2SQL, a benchmark covering six major database systems with 2,218 dialect-specific test cases. Experimental results show that Dial consistently improves translation accuracy by 10.25% and dialect feature coverage by 15.77% over state-of-the-art baselines.

Published in Proceedings of the VLDB Endowment (PVLDB), Vol. 19, No. 11, 2026

Databases (cs.DB); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Information Retrieval (cs.IR); Machine Learning (cs.LG)

arXiv:2603.07449 [cs.DB]

(or arXiv:2603.07449v2 [cs.DB] for this version)

https://doi.org/10.48550/arXiv.2603.07449 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.14778/3836663.3836720 Focus to learn more DOI(s) linking to related resources

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