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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 ({'are'}) and 1 missing columns ({'what'}).

This happened while the csv dataset builder was generating data using

hf://datasets/rungalileo/mit_movies_fixed_connll_format/MIT_movies_fixed_test.tsv (at revision bf6c430a8673a2305638576a61f99efdd4f7b2a1)

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
              are: string
              O: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 471
              to
              {'what': Value(dtype='string', id=None), 'O': 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 new columns ({'are'}) and 1 missing columns ({'what'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/rungalileo/mit_movies_fixed_connll_format/MIT_movies_fixed_test.tsv (at revision bf6c430a8673a2305638576a61f99efdd4f7b2a1)
              
              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.

what
string
O
string
movies
O
star
O
bruce
B-ACTOR
willis
E-ACTOR
show
O
me
O
films
O
with
O
drew
B-ACTOR
barrymore
E-ACTOR
from
O
the
O
1980s
S-YEAR
what
O
movies
O
starred
O
both
O
al
B-ACTOR
pacino
E-ACTOR
and
O
robert
B-ACTOR
deniro
E-ACTOR
find
O
me
O
all
O
of
O
the
O
movies
O
that
O
starred
O
harold
B-ACTOR
ramis
E-ACTOR
and
O
bill
B-ACTOR
murray
E-ACTOR
find
O
me
O
a
O
movie
O
with
O
a
O
quote
O
about
O
baseball
O
in
O
it
O
what
O
movies
O
have
O
mississippi
S-TITLE
in
O
the
O
title
O
show
O
me
O
science
B-GENRE
fiction
I-GENRE
films
E-GENRE
directed
O
by
O
steven
B-DIRECTOR
spielberg
E-DIRECTOR
do
O
you
O
have
O
any
O
thrillers
S-GENRE
directed
O
by
O
sofia
B-DIRECTOR
coppola
E-DIRECTOR
what
O
leonard
B-SONG
cohen
I-SONG
songs
E-SONG
have
O
been
O
used
O
in
O
a
O
movie
O
show
O
me
O
films
O
elvis
S-ACTOR
films
O
set
B-PLOT
in
I-PLOT
hawaii
E-PLOT
what
O
movie
O
is
O
references
O
zydrate
S-PLOT
are
O
there
O
any
O
musical
B-GENRE
films
E-GENRE
with
O
End of preview.

Dataset Card for MIT_movies_fixed

Dataset Summary

This dataset is a version of the MIT movies

Curation Rationale

This dataset was created to showcase the power of Galileo as a Data Intelligence Platform. Through Galileo, we identify critical error patterns within the original MIT movies dataset - annotation errors, ill-formed samples etc. Moreover, we observe that these errors permeate throughout the test dataset. As a result of our analysis, we fix 4% of the dataset by re-annotating the samples, and provide the dataset for NER research. To learn more about the process of fixing this dataset, please refer to our Blog.

Dataset Structure

Data Instances

Every sample is blank line separated, every row is tab separated, and contains the word and its corresponding NER tag. This dataset uses the BIOES tagging schema.

An example from the dataset looks as follows:

show	O
me	O
a	O
movie	O
about	O
cars	B-PLOT
that	I-PLOT
talk	E-PLOT

Data Splits

The data is split into a training and test split. The training data has ~9700 samples and the test data has ~2700 samples.

Data Classes

The dataset contains the following 12 classes: ACTOR, YEAR, TITLE, GENRE, DIRECTOR, SONG, PLOT, REVIEW, CHARACTER, RATING, RATINGS_AVERAGE, TRAILER. Some of the classes have high semantic overlap (e.g. RATING/RATINGS_AVERAGE and ACTOR/DIRECTOR).

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