矿山数标产品
“矿山数标” 是煤炭共性技术研究院依托太阳石矿山大模型的文档与多模态解析能力,研发的全新煤炭行业标准服务工具。其核心价值在于通过智能检索、智能核校、智能编写、智能贯标四大功能,实现复杂文档结构化处理,打通数据标准与业务场景的关联通道,激活数据资产,重构业务链路,让标准成为 AI 驱动行业创新的核心引擎。 智能检索:通过对复杂文档内容进行结构化处理,完成数据关系映射与标准知识主题挖掘,精准捕捉用户查询意图,高效匹配并输出标准信息。 智能核校:基于机器可读文档与内容,自动抽取各类文档的段落及条款,辅助用户开展标准编制工作,快速识别文本疏漏,确保标准编制符合规范性要求。 智能编写:针对具体应用场景,通过深度挖掘与关联分析,捕捉标准文案数据间的内在联系,辅助用户起草标准草案,大幅提升工作效率。 智能贯标:通过数据映射规范煤炭领域数据标准体系中的数据源属性及属性描述,提供数据字段自动匹配、数据测点自主配置、贯标完成率分析等功能,助力用户高效完成数据贯标任务。
The "Mine Data Standardization Product" is a groundbreaking standardization service tool developed by the Coal Common Technology Research Institute, leveraging the document processing and multimodal analysis capabilities of the Sunstone Mining Large Model. Its core value lies in four key functions: intelligent retrieval, verification, drafting, and standard implementation. These capabilities enable structured processing of complex documents, bridge the gap between data standards and business scenarios, activate data assets, and reconfigure business workflows, ultimately transforming standards into the core engine for AI-driven industry innovation. Intelligent Search: By structuring complex document content, it completes data relationship mapping and standard knowledge topic mining, accurately captures user query intent, and efficiently matches and outputs standard information. Smart Verification: Automatically extracts paragraphs and clauses from machine-readable documents and content to assist users in standard development, quickly identifying text omissions and ensuring compliance with normative requirements. Smart Drafting: For specific use cases, it deeply mines and analyzes correlations to identify inherent connections between standard copy data, helping users draft standard drafts and significantly improving work efficiency. Smart Standardization: By mapping data to standardize data source attributes and descriptions in the coal industry's data standard system, it provides features like automatic data field matching, self-configurable measurement points, and analysis of standardization completion rates, helping users efficiently complete data standardization tasks.

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