The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: OverflowError
Message: value too large to convert to int32_t
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 4195, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2533, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2711, in iter
for key, pa_table in ex_iterable.iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2249, in _iter_arrow
yield from 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/json/json.py", line 237, in _generate_tables
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/_json.pyx", line 54, in pyarrow._json.ReadOptions.__init__
File "pyarrow/_json.pyx", line 79, in pyarrow._json.ReadOptions.block_size.__set__
OverflowError: value too large to convert to int32_tNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
APR Criminal Case Database (Chinese)
Dataset Description
This dataset is constructed to support Analogical Precedent Retrieval (APR). It comprises 172,445 real-world criminal cases spanning from 2001 to 2020, covering 25 provinces in China. The extensive corpus provides sufficient geographical and temporal diversity for robust analogical retrieval research.
Acknowledgments
We would like to express our sincere gratitude to the open-source project liuhuanyong/LawCrimeMining (Law Crime Mining Based on Corpus build and content analysis by NLP methods). Our data collection pipeline was adapted based on their foundational work. The raw legal documents were primarily collected from public legal databases, including Lawlib. We crawled and processed these publicly available judicial records strictly for academic, non-commercial research purposes.
Ethical Considerations & Privacy
The dataset consists of judicial decisions that are inherently public records. To protect individual privacy and strictly comply with academic ethical guidelines, all case documents have been thoroughly anonymized to remove sensitive personal information (e.g., real names of individuals, specific identification numbers). The dataset is released solely for academic research purposes—specifically to evaluate NLP algorithms and mitigate LLM hallucinations—and strictly prohibits any commercial application or malicious use.
- Downloads last month
- 11