5W1H+Which：渐进式本体绑定的上下文有效语义索引
5W1H+Which: Context-Valid Semantic Indexing with Progressive Ontology Binding
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中文总结 AI 辅助
提出5W1H+Which语义索引，分离内容提取与本体绑定，通过渐进式绑定和上下文约束提升跨任务证据覆盖，并计划用事实图基线验证其可测试性。
中文摘要 AI 辅助
将原始数据转化为可查询的知识，既需要早期提取可复用的信息，也需要针对特定任务的显式类型、关系及适用条件。如果索引过早地围绕单一业务模式选择内容，后续任务可能无法使用被遗漏的信息。然而，如果索引仅保留开放式文本，基于规则的推理则缺乏可检查的前提。我们提出5W1H+Which，一种将内容提取与本体绑定分离的语义索引设计。5W1H问题组织基于源的内容单元；Which指向版本化的本体元素，并记录映射关系、范围和验证状态。时间、位置、系统环境和参与者角色不仅仅是检索标签：它们共同约束了事实、绑定和规则适用的上下文。未绑定的内容保持可搜索，而绑定的内容仅在前提检查后进入正式推理路径。该方法进一步区分业务有效时间、系统知识时间和操作痕迹，并使用依赖记录支持绑定重新验证和派生结论的维护。一个从本地服务器迁移到云环境的示例说明了世界状态变化、本体版本变化和规则适用性变化的不同处理方式。我们提出了三组关于跨任务证据覆盖、上下文误用控制和增量更新成本的可证伪假设。计划中的评估包括一个具有相同证据、时间信息和预算的强类型事实图基线，以测试收益是否来自5W1H组织、延迟绑定或额外的信息和工程努力。该贡献是一种可测试的索引机制，而非声称新的通用本体或展示的性能优势。
英文摘要
Transforming raw data into queryable knowledge requires both early extraction of reusable information and explicit types, relations, and applicability conditions for particular tasks. If indexing selects content too early around a single business schema, later tasks may be unable to use information that was omitted. If the index retains only open-ended text, however, rule-based reasoning lacks checkable premises. We propose 5W1H+Which, a semantic indexing design that separates content extraction from ontology binding. The 5W1H questions organize source-grounded content units; Which points to versioned ontology elements and records mapping relations, scope, and validation status. Time, location, system environment, and participant roles are not merely retrieval labels: together, they constrain the contexts in which facts, bindings, and rules apply. Unbound content remains searchable, while bound content enters a formal reasoning path only after premise checks. The method further distinguishes business valid time, system knowledge time, and operational traces, and uses dependency records to support binding revalidation and the maintenance of derived conclusions. A worked example of migration from an on-premises server to a cloud environment illustrates the different treatment of world-state changes, ontology-version changes, and changes in rule applicability. We formulate three groups of falsifiable hypotheses concerning cross-task evidence coverage, control of contextual misuse, and incremental update cost. The planned evaluation includes a strong typed fact-graph baseline with the same evidence, temporal information, and budget, to test whether benefits arise from 5W1H organization, deferred binding, or additional information and engineering effort. The contribution is a testable indexing mechanism, not a claim to a new universal ontology or a demonstrated performance advantage.
发表机构
- PwC China AI Center（普华永道中国人工智能中心）
- Tsinghua University（清华大学）
机构由 AI 辅助整理，请以论文原文为准。
