这篇论文给AI代理装上了'权限检查器'，用五域本体和DNA系数解决'能不能做'和'该不该做'的问题，搞AI治理的值得一看。
该论文提出权威解析框架（ARF），一个五域本体论，用于表示和解析组织角色、业务流程、机器权限及外部环境中的权威。ARF引入权威关系（AR）作为跨域原语，包含行动者、行动、对象、边界上下文、理由链和DNA系数（衡量文档权威与实际实践的偏差）。框架提供JSON-LD表示和知识图谱查询模式，支持AI代理在执行重要行动前确定权威的来源、范围和上下文有效性。论文将权威解析定位为知识表示与推理问题，处于本体工程、语义AI、代理AI和AI治理的交汇点。
The Authority Resolution Framework: A Five-Domain Ontology for Governing Who and What Decides, at Scale
As AI systems become increasingly capable of autonomous action, determining whether an agent is technically capable of performing an action is insufficient: the system must also determine whether the action is authorised in its context. This paper introduces the Authority Resolution Framework (ARF), a five-domain ontology for representing and resolving authority across organisational roles and informal influence, business concepts, codified processes, machine-readable permissions and executable systems, and external real-world context. ARF defines the Authority Relation (AR) as a cross-domain primitive binding an actor, action, object, bounded context, justification chain, and a calibration measure termed the DNA-Coefficient, which captures divergence between documented authority structures and authority as practiced. The framework provides a machine-interpretable representation of authority provenance and scope, with JSON-LD representations and knowledge-graph query patterns for authority resolution. ARF is designed to support AI agents in determining the provenance, scope and contextual validity of authority before executing consequential actions. The framework positions authority resolution as a knowledge-representation and reasoning problem at the intersection of ontology engineering, semantic AI, agentic AI and AI governance.