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/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, 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__
self.options.block_size = value
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.
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Check out the documentation for more information.
LEGALWORLD Dataset
LEGALWORLD is a lifecycle interactive environment tailored for legal agents, modeled based on China’s civil litigation procedures. It covers successive procedural stages including legal consultation, document drafting, first-instance trial, appeal adjudication, appeal drafting and second-instance trial. This dataset provides case data and legal provision retrieval data to support research on the LEGALWORLD environment and relevant legal agents.
Data File Description
Full_version_raw.json,medium_version_raw.json,light_version_raw.json: The three raw versions contain original case data distinguished only by data scale, applicable to custom information extraction, data cleansing, modeling and experimental construction.light_case_dataset.json: Processed lightweight case dataset with essential information extraction and structuring finished, which can be directly adopted for LEGALWORLD-related tasks and downstream experiments.law_metadata.jsonl: Raw data for legal provision retrieval. Users can generate embeddings for legal provision texts independently, and build legal provision retrieval tools combined with vector databases or retrieval modules.
Relevant Links
Project Page: https://chidaic\.github\.io/Legal\-world/
LEGALWORLD defines civil litigation as an interconnected lifecycle process instead of a set of isolated tasks. The case and legal provision resources in the dataset support research on legal agents’ capabilities in multi-stage litigation workflows, covering legal consultation, legal reasoning, legal document generation, courtroom interaction and legal provision retrieval.
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