Marx’s Intellectual Measure Triple-Algorithm Audit Dataset: Formal Logic – Generative Validation of Intellectual History – Consistency Testing of Contemporary Expressions

This dataset conducts a structured evidence audit of the text based on Liu Tongfang's article ‘Marx's Measure of Thought,’ published in Guangming Daily, using ‘measure’ as the core concept. The audit is verifiable, reproducible, and testable. The data employs a ‘triple algorithmic review process’: formal logical auditing, verification through the generation of intellectual history, and consistency testing against the new era. Utilising a Chinese clause numbering system and rule-driven indicator framework, it quantitatively assesses conceptual semantic stability, the adequacy of phase boundaries, the explicitness of contradiction mechanism chains, and the operational feasibility of mapping to the new era. The dataset outputs include sentence/clause-level annotation tables, rule-triggered logs, and metric result tables. These resources facilitate standardised peer review of philosophical texts, computable assessment of argument strength, and research into verifiable rewriting methodologies.

本数据集以发表于《光明日报》的刘同芳文章《马克思的思想尺度》（Marx's Measure of Thought）为文本基础，以“尺度”（measure）为核心概念，对该文本开展结构化证据审核。该审核具备可验证性、可复现性与可检验性。本数据集采用“三重算法审核流程”：形式逻辑审核、通过思想史生成开展验证，以及针对新时代的一致性检验。本数据集借助中文分句编号体系与规则驱动的指标框架，从概念语义稳定性、阶段边界合理性、矛盾机制链条明晰性以及向新时代映射的操作可行性四个维度开展量化评估。本数据集的输出内容包含句子/分句级标注表、规则触发日志以及指标结果表。这些成果可为哲学文本的标准化同行评议、论证强度的可计算评估以及可验证改写方法论研究提供支撑。