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Error code: FeaturesError Exception: ArrowTypeError Message: ("Expected bytes, got a 'int' object", 'Conversion failed for column answer with type object') Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, 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 array 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 233, 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 2998, 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 1918, 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 2093, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__ for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__ for key, pa_table in self.generate_tables_fn(**gen_kwags): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 167, in _generate_tables pa_table = pa.Table.from_pandas(df, preserve_index=False) File "pyarrow/table.pxi", line 3874, in pyarrow.lib.Table.from_pandas File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 624, in dataframe_to_arrays arrays[i] = maybe_fut.result() File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 439, in result return self.__get_result() File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 391, in __get_result raise self._exception File "/usr/local/lib/python3.9/concurrent/futures/thread.py", line 58, in run result = self.fn(*self.args, **self.kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 598, in convert_column raise e File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/pandas_compat.py", line 592, in convert_column result = pa.array(col, type=type_, from_pandas=True, safe=safe) File "pyarrow/array.pxi", line 339, in pyarrow.lib.array File "pyarrow/array.pxi", line 85, in pyarrow.lib._ndarray_to_array File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowTypeError: ("Expected bytes, got a 'int' object", 'Conversion failed for column answer with type object')
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Dataset Card for ACQAD
we propose a new approach to automatically generate a dataset for Arabic complex question answering task. The proposed approach is based on using an effective workflow with a set of templates. The generated dataset, denoted as ACQAD, contains more than 118k questions, covering both comparison and multi-hop types. Each question-answer pair is decomposed into a set of single-hop questions, allowing QA systems to reduce question complexity and explain the reasoning steps
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Arabic Wikipedia
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BibTeX:
@inproceedings{sidhoum2022acqad, title={ACQAD: a dataset for arabic complex question answering}, author={Hamouda Sidhoum, Abdellah and Mataoui, M’hamed and Sebbak, Faouzi and Sma{"\i}li, Kamel}, booktitle={International conference on cyber security, artificial inteligence and theoretical computer science}, year={2022} }
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