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Error code: DatasetGenerationError Exception: DatasetGenerationError Message: An error occurred while generating the dataset 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 997, 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 1321, 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 935, 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 dataset
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id
string | date
unknown |
---|---|
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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