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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 missing columns ({'licensing'})
This happened while the csv dataset builder was generating data using
hf://datasets/joey234/neg-136/NEG-136-SIMP.tsv (at revision 65312b1ae759cb963e15e67d641b76c975f2da5b)
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
item: int64
context_aff: string
context_neg: string
target_aff: string
target_neg: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 849
to
{'item': Value(dtype='int64', id=None), 'context_aff': Value(dtype='string', id=None), 'context_neg': Value(dtype='string', id=None), 'target_aff': Value(dtype='string', id=None), 'target_neg': Value(dtype='string', id=None), 'licensing': Value(dtype='string', 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 missing columns ({'licensing'})
This happened while the csv dataset builder was generating data using
hf://datasets/joey234/neg-136/NEG-136-SIMP.tsv (at revision 65312b1ae759cb963e15e67d641b76c975f2da5b)
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)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
item
int64 | context_aff
string | context_neg
string | target_aff
string | target_neg
string | licensing
string |
|---|---|---|---|---|---|
0
|
With proper equipment, scuba-diving is very
|
With proper equipment, scuba-diving isn't very
|
safe
|
dangerous
|
Y
|
1
|
Traveling in Baghdad is very
|
Traveling in Baghdad isn't very
|
dangerous
|
safe
|
Y
|
2
|
In moderation, drinking red wine is
|
In moderation, drinking red wine isn't
|
good
|
bad
|
Y
|
3
|
Drinking tap water in developing countries is very
|
Drinking tap water in developing countries isn't very
|
dangerous
|
safe
|
Y
|
4
|
Secondhand furniture is very
|
Secondhand furniture isn't very
|
cheap
|
expensive
|
Y
|
5
|
Most smokers find that quitting is very
|
Most smokers find that quitting isn't very
|
difficult
|
easy
|
Y
|
6
|
Old computers may be
|
Old computers may not be
|
slow
|
fast
|
Y
|
7
|
A fast food dinner on a first date is very
|
A fast food dinner on a first date isn't very
|
lame
|
romantic
|
Y
|
8
|
Bulletproof vests are very
|
Bulletproof vests aren't very
|
safe
|
dangerous
|
N
|
9
|
Terrorist bomb attacks are really
|
Terrorist bomb attacks aren't really
|
dangerous
|
safe
|
N
|
10
|
Vitamins and proteins are very
|
Vitamins and proteins aren't very
|
good
|
bad
|
N
|
11
|
Using strong suntan lotion is
|
Using strong suntan lotion isn't
|
safe
|
dangerous
|
N
|
12
|
Rockets and missiles are very
|
Rockets and missiles aren't very
|
fast
|
slow
|
N
|
13
|
Keeping the door open for somebody is very
|
Keeping the door open for somebody isn't very
|
polite
|
rude
|
N
|
14
|
A baby bunny's fur is very
|
A baby bunny's fur isn't very
|
soft
|
hard
|
N
|
15
|
Businessman Donald Trump is really
|
Businessman Donald Trump isn't really
|
rich
|
poor
|
N
|
0
|
A trout is (a|an)
|
A trout is not (a|an)
|
fish
|
tool
| null |
1
|
A salmon is (a|an)
|
A salmon is not (a|an)
|
fish
|
flower
| null |
2
|
An ant is (a|an)
|
An ant is not (a|an)
|
insect
|
vegetable
| null |
3
|
A bee is (a|an)
|
A bee is not (a|an)
|
insect
|
building
| null |
4
|
A robin is (a|an)
|
A robin is not (a|an)
|
bird
|
tree
| null |
5
|
A sparrow is (a|an)
|
A sparrow is not (a|an)
|
bird
|
vehicle
| null |
6
|
An oak is (a|an)
|
An oak is not (a|an)
|
tree
|
vehicle
| null |
7
|
A pine is (a|an)
|
A pine is not (a|an)
|
tree
|
tool
| null |
8
|
A rose is (a|an)
|
A rose is not (a|an)
|
flower
|
insect
| null |
9
|
A daisy is (a|an)
|
A daisy is not (a|an)
|
flower
|
bird
| null |
10
|
A carrot is (a|an)
|
A carrot is not (a|an)
|
vegetable
|
fish
| null |
11
|
A pea is (a|an)
|
A pea is not (a|an)
|
vegetable
|
building
| null |
12
|
A hammer is (a|an)
|
A hammer is not (a|an)
|
tool
|
insect
| null |
13
|
A saw is (a|an)
|
A saw is not (a|an)
|
tool
|
vegetable
| null |
14
|
A car is (a|an)
|
A car is not (a|an)
|
vehicle
|
tree
| null |
15
|
A truck is (a|an)
|
A truck is not (a|an)
|
vehicle
|
flower
| null |
16
|
A hotel is (a|an)
|
A hotel is not (a|an)
|
building
|
fish
| null |
17
|
A house is (a|an)
|
A house is not (a|an)
|
building
|
bird
| null |
YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
This dataset contains two subsets: NEG-136-SIMP and NEG-136-NAT. NEG-136-SIMP items come from Fischler et al. (1983). NEG-136-NAT items come from Nieuwland & Kuperberg (2008).
The NEG-136-SIMP.tsv and NEG-136-NAT.tsv files contain for each item the affirmative and negative version of the context (context_aff, context_neg), and completions that are true with the affirmative context (target_aff) and with the negative context (target_neg).
- For NEG-136-SIMP, determiners (a/an) are left ambiguous, and need to be selected based on the completion noun (this is done already in
proc_datasets.py).
References:
- Ira Fischler, Paul A Bloom, Donald G Childers, Salim E Roucos, and Nathan W Perry Jr. 1983. Brain potentials related to stages of sentence verification.
- Mante S Nieuwland and Gina R Kuperberg. 2008. When the truth is not too hard to handle: An event-related potential study on the pragmatics of negation.
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