The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
law_number: string
law_article: string
citation_type: string
total_citations: int64
unique_decisions: int64
to
{'law_number': Value('string'), 'law_article': Value('string'), 'degree': Value('int64'), 'pagerank': Value('float64'), 'authority': Value('float64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 209, in _generate_tables
yield Key(file_idx, batch_idx), self._cast_table(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 147, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
law_number: string
law_article: string
citation_type: string
total_citations: int64
unique_decisions: int64
to
{'law_number': Value('string'), 'law_article': Value('string'), 'degree': Value('int64'), 'pagerank': Value('float64'), 'authority': Value('float64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Ukrainian Court Citation Graph (ЄДРСР)
A large-scale co-citation graph derived from 99.5 million Ukrainian court decisions in the Unified State Register of Court Decisions (ЄДРСР / EDRSR).
Overview
This dataset contains the co-citation network of Ukrainian legislation as cited in court decisions from 2003 to 2026. Two legal provisions (articles) are linked if they are cited together in the same court decision. The edge weight reflects how many decisions co-cite the pair.
Source corpus: 99.5M full-text court decisions from reyestr.court.gov.ua Citation extraction: 345M citation rows extracted via regex patterns matching Ukrainian legal citation conventions (codex articles, law articles, constitutional provisions, case references) Co-citation construction: Streaming pairwise combination of articles per decision, filtered to edges with weight >= 10
Dataset Statistics
| Metric | Value |
|---|---|
| Source decisions | 99,500,000 |
| Extracted citations | 345,000,000 |
| Unique article-decision pairs | 36,958,613 |
| Co-citation edges (weight >= 10) | 2,328,213 |
| Unique articles in graph | ~50,000 |
| Time span | 2003 -- 2026 |
Files
cocitation_edges.parquet (9.4 MB)
The core co-citation graph. Each row is an undirected edge between two legal provisions.
| Column | Type | Description |
|---|---|---|
law_a |
string | Name of the first law/codex |
article_a |
string | Article number in the first law |
law_b |
string | Name of the second law/codex |
article_b |
string | Article number in the second law |
weight |
int64 | Number of court decisions co-citing both articles |
article_citation_stats.parquet (0.2 MB)
Top 50,000 most-cited legal provisions with citation counts.
| Column | Type | Description |
|---|---|---|
law_number |
string | Law or codex name |
law_article |
string | Article number |
citation_type |
string | Type: codex_article, law_article, constitution |
total_citations |
int64 | Total citation count across all decisions |
unique_decisions |
int64 | Number of unique decisions citing this article |
article_centrality.parquet
Graph centrality measures for top articles (union of top-50 by degree, PageRank, and HITS authority).
| Column | Type | Description |
|---|---|---|
law_number |
string | Law or codex name |
law_article |
string | Article number |
degree |
int64 | Weighted degree in co-citation graph |
pagerank |
float64 | PageRank score |
authority |
float64 | HITS authority score |
community_labels.parquet
Louvain community detection results across 5 time periods (2007--2010, 2011--2014, 2015--2018, 2019--2022, 2023--2026).
| Column | Type | Description |
|---|---|---|
period |
string | Time period |
community_rank |
int32 | Rank by size within period |
community_size |
int32 | Number of articles in community |
dominant_law |
string | Most frequent law in the community |
dominant_law_fraction |
float64 | Fraction of articles from dominant law |
total_citations |
int64 | Sum of citations across community members |
Key Findings
- Power-law degree distribution with exponent alpha = 2.17 (scale-free network)
- PageRank diverges from raw degree: ст. 10 ЦПК (fair trial) ranks #1 by PageRank but #2 by degree, indicating structural centrality beyond citation frequency
- Community structure tracks legal domains: Louvain modularity 0.54--0.61, with communities aligning to criminal, civil, administrative, and tax law
- Temporal stability: NMI between adjacent periods > 0.85, but post-2017 judicial reform shows community reorganization
- Citation prediction: Logistic regression on graph features achieves AUC = 0.9984 for predicting top-1000 articles in 2020--2026 from 2007--2019 features
Citation
If you use this dataset, please cite:
@misc{kovalenko2026citation,
title={Citation Graph Analysis of 99.5 Million Ukrainian Court Decisions: Co-Citation Networks, Community Structure, and Temporal Dynamics},
author={Ovcharov, Volodymyr},
year={2026},
howpublished={\url{https://huggingface.co/datasets/overthelex/ua-court-citation-graph}},
note={Derived from the Unified State Register of Court Decisions (ЄДРСР)}
}
Related
- overthelex/ua-case-outcome -- Ukrainian court case outcome prediction dataset
- overthelex/oversight-constitution -- Edit-trace oversight constitution dataset
- Paper: Citation Graph Analysis of 99.5M Ukrainian Court Decisions (arXiv, forthcoming)
License
CC-BY-NC-SA-4.0. Academic and research use is free. Commercial use requires separate licensing from legal.org.ua.
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