Half a billion citation edges extracted from 100.7 million Ukrainian court decisions reveal that judicial citation structure encodes legal domain boundaries without supervision and predicts future legislative importance with near-perfect accuracy. We construct the first large-scale citation graph from the complete EDRSR registry (99.5 million full texts, 1.1 TB), extracting 502 million citation links across six types via regex on commodity hardware in approximately 5 hours, with precision of 1.00 on a 200-decision validation sample (95% Wilson CI: [0.982, 1.000]). Three principal findings emerge. (1) The degree distribution follows a power law (alpha = 1.57 +/- 0.008), placing the Ukrainian court network near the EU Court of Justice and below the US Supreme Court, with hub articles cited by millions of decisions. (2) Louvain community detection on the co-citation projection recovers legal domain boundaries (civil, criminal, administrative, commercial) with modularity Q = 0.44-0.55 and temporal stability (NMI = 0.83-0.86 across periods), constituting an automatically constructed legal ontology grounded in judicial practice. (3) Citation features predict top-1000 articles with AUC = 0.9984, substantially outperforming a naive frequency baseline (P@1000 = 0.655); temporal dynamics detect legislative regime changes as phase transitions and the 2022 invasion as a citation entropy spike (H: 11.02 -> 13.49) with emergent wartime legislation nodes. The citation-derived ontology is operationalized as the domain layer of a workflow memory system for LLM-assisted legal analysis, connecting to the ontology-controlled paradigm. The extraction pipeline, analysis code, and aggregated statistics are released as open data.

翻译：从1.007亿份乌克兰法院判决中提取的五亿条引用边表明，司法引用结构无需监督即可编码法律领域边界，并能以近乎完美的准确率预测未来立法重要性。我们基于完整的EDRSR登记系统（9950万份全文文本，1.1 TB）构建了首个大规模引用图谱，通过正则表达式在商用硬件上约5小时内提取了六种类型的5.02亿条引用链接，对200份判决验证样本的精确度为1.00（95% Wilson置信区间：[0.982， 1.000]）。主要发现有三项：(1) 度分布遵循幂律（α=1.57±0.008），使乌克兰法院网络接近欧盟法院水平且低于美国最高法院，核心条款被数百万份判决引用。(2) 对共引投影进行Louvain社区检测后，可恢复法律领域边界（民事、刑事、行政、商事），模块度Q=0.44—0.55且具有时间稳定性（跨时段归一化互信息NMI=0.83—0.86），构成了基于司法实践的自动构建法律本体。(3) 引用特征预测前1000条条款的AUC达0.9984，显著优于朴素频率基线（P@1000=0.655）；时间动态检测到立法制度变迁表现为相变，而2022年入侵事件体现为引用熵峰值（H：11.02→13.49），并出现战时立法节点涌现。该引用衍生本体被实例化为面向大语言模型辅助法律分析的工作流记忆系统的领域层，与本体制导范式相衔接。抽取流水线、分析代码及聚合统计信息均以开放数据形式发布。