Method and system for intelligently generating knowledge query statements driven by large-model and few-sample context learning based on scene awareness

The invention relates to a method and a system for intelligently generating knowledge query statements driven by large-model and few-sample context learning based on scene perception. The method comprises the following steps of: performing logic skeleton analysis on a natural language question, namely a target question, input by a user; retrieving related knowledge components from a knowledge base according to the target question; carrying out few-sample context learning by using a large model to realize selection of knowledge components; and constructing a logic expression according to the logic skeleton and the selected knowledge component to obtain a knowledge query statement. Through combination of scene learning and knowledge query statement generation, not only are the accuracy and execution efficiency of knowledge questions and answers improved, but also the cost is remarkably reduced, and excellent generalization ability and wide application prospects are shown. 本发明涉及一种基于场景感知的大模型少样本上下文学习驱动的知识查询语句智能生成方