The dataset viewer is not available for this split.
Error code: FeaturesError Exception: AttributeError Message: 'str' object has no attribute 'keys' Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute compute_first_rows_from_parquet_response( File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response rows_index = indexer.get_rows_index( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index return RowsIndex( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__ self.parquet_index = self._init_parquet_index( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index response = get_previous_step_or_raise( File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise raise CachedArtifactError( libcommon.simple_cache.CachedArtifactError: The previous step failed. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 122, in _generate_tables pa_table = paj.read_json( File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 240, in compute_first_rows_from_streaming_response iterable_dataset = iterable_dataset._resolve_features() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2216, in _resolve_features features = _infer_features_from_batch(self.with_format(None)._head()) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1239, in _head return _examples_to_batch(list(self.take(n))) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__ yield from islice(self.ex_iterable, self.n) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__ for key, pa_table in self.generate_tables_fn(**self.kwargs): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 173, in _generate_tables f"This JSON file contain the following fields: {str(list(dataset.keys()))}. " AttributeError: 'str' object has no attribute 'keys'
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
The Caselaw Access Project
In collaboration with Ravel Law, Harvard Law Library digitized over 40 million U.S. court decisions consisting of 6.7 million cases from the last 360 years into a dataset that is widely accessible to use. Access a bulk download of the data through the Caselaw Access Project API (CAPAPI): https://case.law/caselaw/
Find more information about accessing state and federal written court decisions of common law through the bulk data service documentation here: https://case.law/docs/
Learn more about the Caselaw Access Project and all of the phenomenal work done by Jack Cushman, Greg Leppert, and Matteo Cargnelutti here: https://case.law/about/
Watch a live stream of the data release here: https://lil.law.harvard.edu/about/cap-celebration/stream
Post-processing
Teraflop AI is excited to help support the Caselaw Access Project and Harvard Library Innovation Lab, in the release of over 6.6 million state and federal court decisions published throughout U.S. history. It is important to democratize fair access to data to the public, legal community, and researchers. This is a processed and cleaned version of the original CAP data.
During the digitization of these texts, there were erroneous OCR errors that occurred. We worked to post-process each of the texts for model training to fix encoding, normalization, repetition, redundancy, parsing, and formatting.
Teraflop AI’s data engine allows for the massively parallel processing of web-scale datasets into cleaned text form. Our one-click deployment allowed us to easily split the computation between 1000s of nodes on our managed infrastructure.
Licensing Information
The Caselaw Access Project dataset is licensed under the CC0 License.
Citation Information
The President and Fellows of Harvard University. "Caselaw Access Project." 2024, https://case.law/
@misc{ccap,
title={Cleaned Caselaw Access Project},
author={Enrico Shippole, Aran Komatsuzaki},
howpublished{\url{https://huggingface.co/datasets/TeraflopAI/Caselaw_Access_Project}},
year={2024}
}
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