Query statement generation method and device, electronic equipment and storage medium
By identifying demand intent and combining language models and database schema information to generate query statements, the problem of high error rate in query statement generation with the assistance of artificial intelligence is solved, and the accuracy of query statements and the efficiency of business services are improved.
CN120743928AActive Publication Date: 2025-10-03INSPUR SUZHOU INTELLIGENT TECH CO LTD
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Patent Information
- Application Number
- CN202511224669.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-29
- Publication Date
- 2025-10-03
- Estimated Expiration
- 2045-08-29
AI Technical Summary
Technical Problem
In database query tasks assisted by artificial intelligence technology, the error rate of query statement generation is high, resulting in reduced business service response efficiency.
Method used
By identifying demand intent based on business data, using language models to generate execution logic structures, combining preset database schema information for semantic understanding, outputting intermediate structured data, and ultimately generating accurate query statements.
Benefits of technology
It improves the accuracy of query statements and the response speed of business services, avoids operations on irrelevant or erroneous database objects, and improves the response efficiency of business services.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides a query statement generation method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence, in particular to the field of computers, the field of databases and the field of deep learning. The query statement generation method comprises the steps of performing intention recognition on a demand text based on business data to obtain a demand intention; in response to the demand intention meeting a preset demand condition, processing the demand intention by using a language model to obtain an execution logic structure, the execution logic structure comprising a plurality of execution logic elements based on structured representation, and a structured relationship among the plurality of execution logic elements representing an execution process of executing the query statement; determining target mode information matched with the text semantics represented by the execution logic element from preset database mode information; performing semantic understanding on the plurality of execution logic elements and the target mode information by utilizing a language model, and outputting a plurality of pieces of intermediate structured data for describing the query statement; and generating a query statement according to the intermediate structured data.
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