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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowNotImplementedError
Message: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 620, in write_table
self._build_writer(inferred_schema=pa_table.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
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.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field.
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/builder.py", line 1886, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 639, in finalize
self._build_writer(self.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
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.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field.
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 1420, 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 1052, 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.
_data_files
list | _fingerprint
string | _format_columns
sequence | _format_kwargs
dict | _format_type
null | _output_all_columns
bool | _split
null |
|---|---|---|---|---|---|---|
[
{
"filename": "data-00000-of-00001.arrow"
}
] | e1fe46091b0589d9 | [
"answers.answer_start",
"answers.text",
"context",
"feat_answers.answer_type",
"feat_id",
"feat_question_type",
"feat_title",
"question"
] | {} | null | false | null |
AutoTrain Dataset for project: tam_jp
Dataset Description
This dataset has been automatically processed by AutoTrain for project tam_jp.
Languages
The BCP-47 code for the dataset's language is ja.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"context": "\u30dd\u30fc\u306f\u30b8\u30e3\u30fc\u30ca\u30ea\u30ba\u30e0\u306e\u6d3b\u767a\u306a\u30dc\u30eb\u30c6\u30a3\u30e2\u30a2\u3092\u751f\u6d3b\u306e\u5834\u306b\u5b9a\u3081\u3001\u30af\u30ec\u30e0\u53d4\u6bcd\u306e\u5bb6\u306b\u5c45\u5019\u3092\u3057\u306a\u304c\u3089(\u5b9f\u5144\u306e\u30a6\u30a3\u30ea\u30a2\u30e0=\u30d8\u30f3\u30ea\u30fc\u306f\u7d50\u6838\u30671831\u5e748\u6708\u306b\u6b7b\u53bb\u3057\u3066\u3044\u305f)\u77ed\u7de8\u5c0f\u8aac\u306e\u57f7\u7b46\u3092\u59cb\u3081\u305f\u30021832\u5e74\u306e1\u6708\u3001\u300e\u30b5\u30bf\u30c7\u30fc\u30fb\u30af\u30aa\u30ea\u30a2\u300f\u8a8c\u306b\u300c\u30e1\u30c3\u30c4\u30a7\u30f3\u30ac\u30fc\u30b7\u30e5\u30bf\u30a4\u30f3\u300d\u304c\u63a1\u7528\u3055\u308c\u3001\u4ee5\u5f8c\u540c\u8a8c\u306b\u300c\u30aa\u30e0\u30ec\u30c3\u30c8\u4faf\u7235\u300d\u300c\u30a8\u30eb\u30b5\u30ec\u30e0\u306e\u7269\u8a9e\u300d\u300c\u606f\u306e\u55aa\u5931\u300d\u300c\u30d0\u30fc\u30b2\u30f3\u306e\u640d\u5931(\u306e\u3061\u300c\u30dc\u30f3\u30dc\u30f3\u300d\u3068\u3057\u3066\u6539\u7b46)\u300d\u304c\u63b2\u8f09\u30011833\u5e74\u304b\u3089\u306f\u300e\u30b5\u30bf\u30c7\u30fc\u30fb\u30f4\u30a3\u30b8\u30bf\u30fc\u300f\u8a8c\u306b\u8a69\u3084\u77ed\u6587\u3092\u63b2\u8f09\u3057\u305f\u3002\u3053\u306e\u9803\u3061\u3087\u3046\u3069\u540c\u300e\u30b5\u30bf\u30c7\u30fc\u30fb\u30f4\u30a3\u30b8\u30bf\u30fc\u300f\u8a8c\u304c\u77ed\u7de8\u3068\u8a69\u306e\u61f8\u8cde\u3092\u6253\u3061\u51fa\u3057\u305f\u305f\u3081\u3001\u30dd\u30fc\u306f\u300e\u30d5\u30a9\u30fc\u30ea\u30aa\u30fb\u30af\u30e9\u30d6\u7269\u8a9e\u300f\u3068\u540d\u3065\u3051\u305f\u77ed\u7de86\u7de8\u3068\u8a69\u3092\u6295\u7a3f\u3001\u3053\u306e\u3046\u3061\u77ed\u7de8\u300c\u58dc\u306e\u4e2d\u306e\u624b\u8a18\u300d\u304c\u6700\u512a\u79c0\u4f5c\u306b\u9078\u3070\u308c\u8cde\u91d150\u30c9\u30eb\u3092\u7372\u5f97\u3057\u305f\u3002\n\n\u3055\u3089\u306b\u30dd\u30fc\u306f\u3001\u3053\u306e\u3068\u304d\u5be9\u67fb\u54e1\u3092\u52d9\u3081\u3066\u3044\u305f\u30dc\u30eb\u30c6\u30a3\u30e2\u30a2\u306e\u8457\u540d\u306a\u653f\u6cbb\u5bb6\u3067\u3042\u308a\u4f5c\u5bb6\u3067\u3042\u3063\u305f\u3001\u30b8\u30e7\u30f3\u30fbP\u30fb\u30b1\u30cd\u30c7\u30a3\u3068\u89aa\u3057\u304f\u306a\u308a\u3001\u5f7c\u306e\u65a1\u65cb\u3067\u30ea\u30c3\u30c1\u30e2\u30f3\u30c9\u306e\u300e\u30b5\u30b6\u30f3\u30fb\u30ea\u30c6\u30e9\u30ea\u30fc\u30fb\u30e1\u30c3\u30bb\u30f3\u30b8\u30e3\u30fc\u300f\u8a8c\u306b\u4f5c\u54c1\u3092\u63b2\u8f09\u3059\u308b\u3088\u3046\u306b\u306a\u3063\u305f\u3002\u3055\u3089\u306b\u305d\u306e\u5f8c\u540c\u8a8c\u306e\u7de8\u96c6\u9577\u304c\u9000\u8077\u3059\u308b\u3068\u3001\u30b1\u30cd\u30c7\u30a3\u306e\u63a8\u85a6\u3067\u300e\u30e1\u30c3\u30bb\u30f3\u30b8\u30e3\u30fc\u300f\u8a8c\u306e\u4e3b\u7b46\u7de8\u96c6\u8005\u3068\u3057\u3066\u8fce\u3048\u3089\u308c\u308b\u3053\u3068\u306b\u306a\u3063\u305f\u3002\u3057\u304b\u3057\u3053\u306e\u9803\u3001\u30dd\u30fc\u306f\u307e\u3060\u5c11\u5973\u3067\u3042\u3063\u305f\u5f93\u59b9\u306e\u30f4\u30a1\u30fc\u30b8\u30cb\u30a2\u3078\u6c42\u5a5a\u3057\u3001\u305d\u308c\u3092\u53d4\u6bcd\u30de\u30e9\u30a4\u30a2\u306b\u62d2\u7d76\u3055\u308c\u3066\u3044\u305f\u3053\u3068\u304b\u3089\u98f2\u9152\u306e\u91cf\u304c\u5897\u3048\u308b\u306a\u3069\u3057\u3066\u5fc3\u60c5\u304c\u8352\u308c\u3066\u304a\u308a\u3001\u300e\u30e1\u30c3\u30bb\u30f3\u30b8\u30e3\u30fc\u300f\u8a8c\u306e\u8077\u3092\u77ed\u671f\u9593\u3067\u8f9e\u3057\u3066\u3057\u307e\u3063\u305f\u3002\u3057\u304b\u3057\u5ea6\u91cd\u306a\u308b\u30dd\u30fc\u306e\u8aac\u5f97\u306b\u30de\u30e9\u30a4\u30a2\u304c\u6298\u308c\u30011833\u5e749\u6708\u306b\u30dc\u30eb\u30c6\u30a3\u30e2\u30a2\u306e\u90e1\u88c1\u5224\u6240\u304b\u3089\u7d50\u5a5a\u8a31\u53ef\u3092\u53d7\u3051\u305f\u3002\u5f53\u6642\u30dd\u30fc\u306f26\u6b73\u3001\u30f4\u30a1\u30fc\u30b8\u30cb\u30a2\u306f\u307e\u3060\u7d50\u5a5a\u4e0d\u53ef\u80fd\u306a13\u6b731\u304b\u6708\u3067\u3042\u3063\u305f\u304c\u3001\u7d50\u5a5a\u8a93\u7d04\u66f8\u306b\u306f21\u6b73\u3068\u8a18\u3055\u308c\u3066\u3044\u305f\u3002",
"question": "\u30dd\u30fc\u306f\u300c\u58dc\u306e\u4e2d\u306e\u624b\u8a18\u300d\u304c\u6700\u512a\u79c0\u4f5c\u306b\u9078\u3070\u308c\u308b\u3053\u3069\u3067\u8cde\u91d1\u3044\u304f\u3089\u3092\u7372\u5f97\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3057\u305f\u304b\u3002",
"answers.text": [
"50\u30c9\u30eb"
],
"answers.answer_start": [
315
],
"feat_id": [
"tr-170-08-002"
],
"feat_title": [
"\u30a8\u30c9\u30ac\u30fc\u30fb\u30a2\u30e9\u30f3\u30fb\u30dd\u30fc"
],
"feat_question_type": [
"Syntactic variation"
],
"feat_answers.answer_type": [
[
"Object"
]
]
},
{
"context": "\u56fd\u969b\u9023\u5408\u98df\u7ce7\u8fb2\u696d\u6a5f\u95a2(FAO)\u306e\u7d71\u8a08\u306b\u3088\u308c\u3070\u30011950\u5e74\u4ee3\u306b\u306f10\u4e07\u30c8\u30f3\u4f59\u308a\u3067\u3042\u3063\u305f\u4e16\u754c\u306e\u30ca\u30de\u30ba\u76ee\u9b5a\u985e\u306e\u7dcf\u6f01\u7372\u91cf\u306f\u5e74\u3005\u5897\u52a0\u3057\u30011990\u5e74\u4ee3\u5f8c\u534a\u306b\u306f100\u4e07\u30c8\u30f3\u3092\u8d85\u3048\u305f\u3002\n2000\u5e74\u4ee3\u4ee5\u964d\u3082\u5897\u52a0\u306e\u52e2\u3044\u306f\u8870\u3048\u305a\u30012000\u5e74\u306b120\u4e07\u30c8\u30f3\u3060\u3063\u305f\u4e16\u754c\u306e\u7dcf\u6f01\u7372\u91cf\u306f\u30012006\u5e74\u306e\u6642\u70b9\u3067\u500d\u4ee5\u4e0a\u306e260\u4e07\u30c8\u30f3\u306b\u9054\u3057\u3066\u3044\u308b\u3002\n\u5730\u57df\u5225\u306b\u898b\u308b\u3068\u30a2\u30b8\u30a2\u30fb\u30a2\u30d5\u30ea\u30ab\u5730\u57df\u3067\u306e\u4f38\u3073\u304c\u9855\u8457\u3067\u3001\u7279\u306b\u30a2\u30b8\u30a2\u3067\u306f2000\u301c2006\u5e74\u306b\u304b\u3051\u3066\u7d043\u500d\u306e\u5897\u52a0(60\u4e07\u30c8\u30f3\u2192180\u4e07\u30c8\u30f3)\u3092\u8a18\u9332\u3057\u3066\u3044\u308b\u3002\n\u540c\u3058\u671f\u9593\u306b\u304a\u3044\u3066\u3001\u5357\u5317\u30a2\u30e1\u30ea\u30ab\u3067\u306f40\u4e07\u30c8\u30f3\u53f0\u3001\u30e8\u30fc\u30ed\u30c3\u30d1\u3067\u306f1\u4e07\u30c8\u30f3\u53f0\u3067\u5927\u304d\u306a\u5909\u52d5\u3082\u306a\u304f\u63a8\u79fb\u3057\u3066\u304a\u308a\u3001\u8fd1\u5e74\u306e\u30a2\u30b8\u30a2\u5730\u57df\u306e\u4f38\u3073\u304c\u7a81\u51fa\u3057\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308b\u3002",
"question": "\u4e16\u754c\u306e\u30ca\u30de\u30ba\u76ee\u9b5a\u985e\u306e\u7dcf\u6f01\u7372\u91cf\u304c\u591a\u304b\u3063\u305f\u306e\u306f1950\u5e74\u4ee3\u30681990\u5e74\u4ee3\u5f8c\u534a\u306e\u3069\u3061\u3089\u3067\u3057\u305f\u304b?",
"answers.text": [
"1990\u5e74\u4ee3\u5f8c\u534a"
],
"answers.answer_start": [
63
],
"feat_id": [
"tr-419-18-000"
],
"feat_title": [
"\u30ca\u30de\u30ba\u76ee"
],
"feat_question_type": [
"Logical reasoning"
],
"feat_answers.answer_type": [
[
"Date/Time"
]
]
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"context": "Value(dtype='string', id=None)",
"question": "Value(dtype='string', id=None)",
"answers.text": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"answers.answer_start": "Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None)",
"feat_id": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"feat_title": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"feat_question_type": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"feat_answers.answer_type": "Sequence(feature=Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), length=-1, id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
|---|---|
| train | 25396 |
| valid | 10289 |
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