LLM-based cross-border appeal text generation method, apparatus and device, and storage medium
By using an LLM-based method for generating cross-border appeal texts, which utilizes legal knowledge graphs and logical expressions to detect conflicts in legal provisions and automatically generate appeal texts, the method solves the problems of time-consuming, labor-intensive, and error-prone traditional methods, thereby improving the efficiency and accuracy of appeal texts.
CN120975984APending Publication Date: 2025-11-18SHENZHEN MINGXIN DIGITAL TECH CO LTD
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Patent Information
- Application Number
- CN202511500763.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-21
- Publication Date
- 2025-11-18
AI Technical Summary
Technical Problem
Traditional methods for generating cross-border appeal texts rely on human experience, which is time-consuming, labor-intensive, and prone to omissions or errors, making it difficult to effectively handle complex cross-border cases.
Method used
The content of cross-border cases is extracted by LLM model and mapped to legal knowledge graph, logical expressions are generated and conflict detection is performed to identify conflicts between legal clauses and automatically generate appeal text.
Benefits of technology
It enables timely identification of logical conflicts between legal provisions, reduces legal risks caused by misunderstandings, improves the efficiency of drafting appeal documents, and ensures the accuracy and legality of appeal documents.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention relates to the technical field of cross-border appeal text generation based on LLM, and discloses an LLM-based cross-border appeal text generation method, device and equipment and a storage medium, the method comprises the following steps: extracting case information, mapping the case information to a legal knowledge graph, generating a logic expression, and carrying out conflict detection, so as to identify conflicts among legal clauses, and finally generating a cross-border appeal text. And generating a complaint text according to the conflicted target legal clause information. The method has the advantages that logic conflicts among related legal clauses are recognized in time, legal risks caused by understanding deviation or improper clause selection are reduced, complaint text compiling efficiency is remarkably improved, case information is automatically extracted, corresponding complaint texts are generated, and working time is shortened.
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