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The dataset generation failed because of a cast error

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'centerpiece'}) and 1 missing columns ({'question'}).

This happened while the json dataset builder was generating data using

hf://datasets/brucewlee1/htest-start-vowel/test.json (at revision ffea224d3fca076ef15a48f13f6c3a1d3a0e7ddb)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
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 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              centerpiece: string
              options: list<item: string>
                child 0, item: string
              correct_options: list<item: string>
                child 0, item: string
              correct_options_literal: list<item: string>
                child 0, item: string
              correct_options_idx: list<item: int64>
                child 0, item: int64
              to
              {'question': Value(dtype='string', id=None), 'options': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'correct_options': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'correct_options_literal': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'correct_options_idx': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              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 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'centerpiece'}) and 1 missing columns ({'question'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/brucewlee1/htest-start-vowel/test.json (at revision ffea224d3fca076ef15a48f13f6c3a1d3a0e7ddb)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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question string	options sequence	correct_options sequence	correct_options_literal sequence	correct_options_idx sequence
Island sings to the city brightly.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Giraffe travels with passion melodiously.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Orchestra travels in the morning enthusiastically.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Robot paints in the park brightly.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Internet flows in the forest accurately.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Cupcake cooks through the telescope happily.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Olive drives with precision eagerly.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Basket flows through the telescope adventurously.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Acrobat observes in the forest attentively.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Yacht paints in the park attentively.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Omelette runs in the morning skillfully.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
River paints in the forest happily.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Airport ticks in the kitchen brightly.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Kite reads in the forest skillfully.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Octopus flows very quickly brightly.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Violin sleeps in the park steadily.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Elevator paints with passion accurately.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Car jumps in the morning steadily.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Artist travels along the valley fast.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Kangaroo cooks in space attentively.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Umbrella teaches in the park happily.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Bicycle cooks in the studio happily.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Eagle runs with interest gracefully.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Balloon sleeps in the hall smoothly.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Urchin glows delicious meals steadily.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Book jumps with passion eagerly.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Umpire jumps with interest carefully.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Car listens to music gracefully.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Acrobat sleeps with precision creatively.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Globe calculates on the wall melodiously.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Elevator cooks on the wall eagerly.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Computer observes to music expertly.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Economist grows every second happily.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Kite flows in the kitchen gracefully.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Albatross calculates in the forest gracefully.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Kangaroo listens in the hall melodiously.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Underdog dances with precision enthusiastically.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Mountain cooks in the morning quietly.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Orchestra jumps to music consistently.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Lion teaches with passion gracefully.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Explorer cooks in the sky adventurously.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Scientist listens on the wall quietly.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Umpire glows every second steadily.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Kangaroo grows in the hall intently.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Idea teaches all night smoothly.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Teacher sings every second attentively.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Alchemist glows in the studio happily.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Tree sings on the wall steadily.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]
Apple cooks in space eagerly.	[ "A", "B" ]	[ "A" ]	[ "A" ]	[ 0 ]
Bicycle dances delicious meals melodiously.	[ "A", "B" ]	[ "B" ]	[ "B" ]	[ 1 ]

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