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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Failed to parse string: '2017-01-21T18:43:18+00:00' as a scalar of type timestamp[s]: expected no zone offset.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature
return array_cast(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1963, in array_cast
return array.cast(pa_type)
File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast
return call_function("cast", [arr], options, memory_pool)
File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call
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: Failed to parse string: '2017-01-21T18:43:18+00:00' as a scalar of type timestamp[s]: expected no zone offset.
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 1529, 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 1154, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2038, 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.
id
string | date
timestamp[us] |
|---|---|
clueweb09-en0035-27-08393 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04271 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11774 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10459 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35625 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00434 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33059 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04272 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11775 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10460 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35626 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00435 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33060 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04273 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11776 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10461 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35627 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00436 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33061 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04274 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11777 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10462 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35628 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00437 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33062 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11778 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10463 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35629 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00438 | 0001-01-01T00:00:00 |
clueweb09-en0112-30-31438 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33063 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11779 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10464 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00439 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33064 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04277 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11780 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10465 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35631 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00440 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33065 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04278 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11781 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10466 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35632 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00441 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33066 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04279 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11782 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10467 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35633 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00442 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33067 | 0001-01-01T00:00:00 |
clueweb09-en0021-70-06592 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04280 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11783 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10468 | 0001-01-01T00:00:00 |
clueweb09-en0104-22-35634 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00443 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33068 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04181 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11684 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00464 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33089 | 0001-01-01T00:00:00 |
clueweb09-en0021-70-06593 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04281 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11784 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10469 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00444 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33069 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04282 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11785 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10470 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00445 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33070 | 0001-01-01T00:00:00 |
clueweb09-en0119-07-05378 | 0001-01-01T00:00:00 |
clueweb09-en0021-70-06595 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04283 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11786 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10471 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00446 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33071 | 0001-01-01T00:00:00 |
clueweb09-en0119-07-05379 | 0001-01-01T00:00:00 |
clueweb09-en0021-70-06596 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04284 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11787 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10472 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00447 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33072 | 0001-01-01T00:00:00 |
clueweb09-en0021-70-06597 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04285 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11788 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10473 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00448 | 0001-01-01T00:00:00 |
clueweb09-en0118-07-33073 | 0001-01-01T00:00:00 |
clueweb09-en0119-07-05381 | 0001-01-01T00:00:00 |
clueweb09-en0049-35-04286 | 0001-01-01T00:00:00 |
clueweb09-en0063-37-11789 | 0001-01-01T00:00:00 |
clueweb09-en0091-60-10474 | 0001-01-01T00:00:00 |
clueweb09-en0104-89-00449 | 0001-01-01T00:00:00 |
End of preview.
Clueweb09 and NeuCLIR1 document dates for reproducing PLAID SHIRTTT
This dataset contains the dates of each document in Clueweb09 and NeuCLIR1 for reproducing experiments in the PLAID SHIRTTT paper (accepted at SIGIR 2024).
For reproducibility, we release the document IDs of the collection divided into shards where there is a file per shard. The creation date of each document is extracted and recorded in ISO format along with the document ID.
For combining the retrieval results from each shard, please refer to the PLAID-X for reference implementation.
Citation
If you use the dates released in this dataset, please consider citing our paper.
@inproceedings{plaid-shirttt,
author = {Dawn Lawrie and Efsun Kayi and Eugene Yang and James Mayfield and and Douglas W. Oard},
title = {PLAID SHIRTTT for Large-Scale Streaming Dense Retrieval},
booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (Short Paper)},
year = {2024},
doi = {??}
}
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