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UA-StatuteRetrieval: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations

A large-scale benchmark for evaluating temporal stability of legal statute retrieval methods. Ground truth is derived exhaustively from 396 million codex-article citations extracted from 101 million Ukrainian court decisions (2007--2026).

Paper: Temporal Decay of Co-Citation Predictability: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations (Ovcharov, 2025)

Dataset Configs

Config Description Rows
article_performance Per-article MRR, Hit@5, degree for 3,667 articles (2024 snapshot) 3,667
ablation_comparison Original / fixed-article / train-test MRR per year (2008--2024) 9
sliding_window Mitigation experiment: MRR by eval year x window size (1, 3, 5, 10, all) 30
embedding_drift Per-article semantic drift (cosine distance 2012 -> 2024) via E5-large 116

Key Findings

  1. Co-citation predictability decays 33--47% over 12 years (Mann-Kendall p < 0.005)
  2. Decay is non-uniform: criminal procedure maintains stable co-citation patterns (MRR ~0.40); civil law degrades from 0.35 to 0.15
  3. Neither BM25 nor dense retrieval (E5-large, BGE-M3) escapes temporal degradation
  4. Sliding-window mitigation improves MRR by 3--28% over cumulative indexing

Evaluation Protocol

Leave-one-out on the full bipartite citation graph:

For each court decision with cited articles {a1, ..., an}:

  1. Mask each article ai in turn
  2. Score all candidate articles using remaining citations as seed
  3. Compute rank of masked article among non-seed candidates

Baselines (2024 snapshot)

Method Hit@10 MRR
Adamic-Adar 0.545 0.272
Common Neighbors 0.534 0.266
E5-large (dense) 0.192 0.090
BGE-M3 (dense) 0.240 0.096
BM25 (lexical) 0.082 0.047
Degree Baseline 0.111 0.059

Difficulty Stratification

Bin Articles MRR (AA)
Hub (>100K cites) 21 0.536
High (10K--100K) 354 0.274
Mid (1K--10K) 864 0.074
Low (100--1K) 1,689 0.020
Rare (<100) 739 0.010

Usage

from datasets import load_dataset

# Per-article performance (2024)
articles = load_dataset("overthelex/ua-statute-retrieval", "article_performance", split="train")
print(articles.to_pandas()[["target_article", "degree", "mrr_aa"]].head(10))

# Temporal ablation (Fig 2 in paper)
ablation = load_dataset("overthelex/ua-statute-retrieval", "ablation_comparison", split="train")
print(ablation.to_pandas())

# Sliding-window mitigation (Table 6 in paper)
sw = load_dataset("overthelex/ua-statute-retrieval", "sliding_window", split="train")
print(sw.to_pandas().pivot(index="eval_year", columns="window_label", values="mrr_aa"))

# Embedding drift (Fig 9 in paper)
drift = load_dataset("overthelex/ua-statute-retrieval", "embedding_drift", split="train")
print(drift.to_pandas().groupby("law_number")["drift"].mean().sort_values(ascending=False))

Citation

@article{ovcharov2025statute,
  title={Temporal Decay of Co-Citation Predictability: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations},
  author={Ovcharov, Volodymyr},
  year={2025}
}

Source Data

Derived from the Ukrainian Unified State Register of Court Decisions (EDRSR, https://reyestr.court.gov.ua). Raw citation data (502M records) remains proprietary; the co-citation graph is available separately at overthelex/ua-court-citation-graph.

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