---
title: "How well does DeepSeek generate SQL when database column names are ambiguous?"  
description: "How well does DeepSeek generate SQL when database column names are ambiguous?"  
author: "Marta Kowalska"  
published: 2026-10-15  
updated: 2026-10-15  
canonical: https://www.mindstick.com/forum/162335/how-well-does-deepseek-generate-sql-when-database-column-names-are-ambiguous  
category: "DeepSeek"  
tags: ["DeepSeek", "sql", "Database Development"]  
reading_time: 1 minute  

---

# How well does DeepSeek generate SQL when database column names are ambiguous?

Has anyone tested DeepSeek on natural-language-to-SQL tasks where the schema is a little messy? I’m thinking of real databases with names like `status`, `type`, or `created_at` appearing in several tables, rather than a clean demo schema.

Does it usually ask for clarification when a request could map to more than one column, or does it confidently choose one? I’d also like to hear whether including **[table relationships](https://www.mindstick.com/blog/475/table-relationships-in-access)** and a few sample rows makes a noticeable difference. This is for an internal reporting tool, so a plausible but incorrect query would be a bigger problem than a request for clarification.


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Original Source: https://www.mindstick.com/forum/162335/how-well-does-deepseek-generate-sql-when-database-column-names-are-ambiguous

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