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Error code: DatasetGenerationError
Exception: ValueError
Message: Failed to convert pandas DataFrame to Arrow Table from file /tmp/hf-datasets-cache/medium/datasets/48937903832340-config-parquet-and-info-zhengyun21-PMC-Patients-M-e8bea6f2/hub/datasets--zhengyun21--PMC-Patients-MetaData/snapshots/23f802e6212503fef847e666876495fdc577111b/PMC-Patients_human_eval.json.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1854, in _prepare_split_single
for _, table in generator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 172, in _generate_tables
raise ValueError(
ValueError: Failed to convert pandas DataFrame to Arrow Table from file /tmp/hf-datasets-cache/medium/datasets/48937903832340-config-parquet-and-info-zhengyun21-PMC-Patients-M-e8bea6f2/hub/datasets--zhengyun21--PMC-Patients-MetaData/snapshots/23f802e6212503fef847e666876495fdc577111b/PMC-Patients_human_eval.json.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed 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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Meta data for PMC-Patients that might facilitate reproduction or usage of our dataset, consisting of the following files (most of which can be derived from our main files above).
PMIDs.json
PMIDs of articles from which PMC-Patients are extracted. List of string, length 140,897.
train_PMIDs.json & dev_PMIDs.json & test_PMIDs.json
PMIDs of articles in training / dev / test split. List of string.
train_patient_uids.json & dev_patient_uids.json & test_patient_uids.json
Patient_uids of notes in training / dev / test split. List of string.
patient2article_relevance.json
Full patient-to-article dataset.
A dict where the keys are patient_uid of queries and each entry is a list of PMID, representing articles relevant to the query.
The 3-point relevance can be obtained by checking whether the PMID is in PMIDs.json.
patient2patient_similarity.json
Full patient-to-patient similarity dataset.
A dict where the keys are patient_uid of queries and each entry is a list of patient_uid, representing similar patients to the query.
The 3-point similarity can be obtained by checking whether the similar patient share the PMID (the string before '-' in patient_uid) with the query patient.
PMID2Mesh.json
Dict of PMIDs to MeSH terms of the article.
MeSH_Humans_patient_uids.json
patient_uid of the patients in PMC-Patients-Humans (extracted from articles with "Humans" MeSH term).
List of string.
PMC-Patients_citations.json
Citations for all articles we used to collect our dataset.
A dict where the keys are patient_uid and each entry is the citation of the source article.
human_PMIDs.json
PMIDs of the 500 randomly sampled articles for human evaluation. List of string.
PMC-Patients_human_eval.json
Expert annotation results of the 500 articles in human_PMIDs.json, including manually annotated patient note, demographics, and relations of the top 5 retrieved articles / patients.
List of dict, and the keys are almost identical to PMC-Patients.json, with the exception of human_patient_id and human_patient_uid.
The relational annotations are different from automatic ones. They are strings indicating on which dimension(s) are the patient-article / patient-patient pair relevant / similar. "0", "1", "2", and "3" represent "Irrelevant", "Diagnosis", "Test", "Treatment" in ReCDS-PAR, and represent "Dissimilar", "Features", "Outcomes", "Exposure" in ReCDS-PPR. Note that a pair can be relevant / similar on multiple dimensions at the same time.
PAR_PMIDs.json
PMIDs of the 11.7M articles used as PAR corpus. List of string.
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