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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 2 new columns ({'DET', 'Die'}) and 2 missing columns ({'PROPN', '•'}). This happened while the csv dataset builder was generating data using hf://datasets/stefan-it/co-funer/dev.tsv (at revision 2b7ab02b5b7ad35aa13c26e3e6da306f16ee4049) 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 Die: string DET: string O: string -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 576 to {'•': Value(dtype='string', id=None), 'PROPN': 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 1577, 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 1191, 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 2 new columns ({'DET', 'Die'}) and 2 missing columns ({'PROPN', '•'}). This happened while the csv dataset builder was generating data using hf://datasets/stefan-it/co-funer/dev.tsv (at revision 2b7ab02b5b7ad35aa13c26e3e6da306f16ee4049) 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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•
string | PROPN
string | O
string |
---|---|---|
Interne | PROPN | B-Auslagerung |
Revision | NOUN | I-Auslagerung |
an | ADP | O |
AIDA | PROPN | B-Unternehmen |
Cruises | PROPN | I-Unternehmen |
- | PUNCT | I-Unternehmen |
German | PROPN | I-Unternehmen |
Branch | PROPN | I-Unternehmen |
of | PROPN | I-Unternehmen |
Costa | PROPN | I-Unternehmen |
Crociere | PROPN | I-Unternehmen |
S.p | PROPN | I-Unternehmen |
. | PUNCT | I-Unternehmen |
A. | X | I-Unternehmen |
• | NOUN | O |
Beratung | NOUN | B-Auslagerung |
in | ADP | I-Auslagerung |
Rechts- | X | I-Auslagerung |
, | PUNCT | I-Auslagerung |
Compliance- | X | I-Auslagerung |
und | CCONJ | I-Auslagerung |
Geldwäsche | ADJ | I-Auslagerung |
Fragen | NOUN | O |
an | ADP | O |
F.lli | PROPN | B-Unternehmen |
Claudio | PROPN | I-Unternehmen |
e | X | I-Unternehmen |
Carlalberto | PROPN | I-Unternehmen |
Corneliani | PROPN | I-Unternehmen |
S.p | PROPN | I-Unternehmen |
. | PUNCT | I-Unternehmen |
A. | X | I-Unternehmen |
• | PROPN | O |
Fondsadministration | NOUN | B-Auslagerung |
an | ADP | O |
HSH | PROPN | B-Unternehmen |
Financial | PROPN | I-Unternehmen |
Markets | PROPN | I-Unternehmen |
Advisory | PROPN | I-Unternehmen |
S.A. | PROPN | I-Unternehmen |
Zweigniederlassung | NOUN | O |
Frankfurt | PROPN | B-Ort |
( | PUNCT | O |
Frankfurt | PROPN | B-Ort |
Branch | PROPN | I-Unternehmen |
) | PUNCT | O |
Folgende | ADJ | O |
Interessenskonflikte | NOUN | O |
könnten | NOUN | O |
sich | PRON | O |
aus | ADP | O |
der | DET | O |
Auslagerung | NOUN | O |
ergeben | VERB | O |
: | PUNCT | O |
• | ADV | O |
Bei | ADP | O |
den | DET | O |
Unternehmen | NOUN | O |
handelt | VERB | O |
es | PRON | O |
sich | PRON | O |
zum | ADP | O |
Teil | NOUN | O |
um | ADP | O |
mit | ADP | O |
der | DET | O |
Gesellschaft | NOUN | O |
verbundene | ADJ | O |
Unternehmen | NOUN | O |
. | PUNCT | I-Unternehmen |
e | X | O |
) | PUNCT | O |
Rechnungswesen | NOUN | B-Auslagerung |
und | CCONJ | O |
technische | ADJ | B-Auslagerung |
Abwicklung | NOUN | I-Auslagerung |
; | PUNCT | O |
f | X | O |
) | PUNCT | O |
Teilbereiche | NOUN | B-Auslagerung |
der | DET | I-Auslagerung |
Informationstechnologie | NOUN | I-Auslagerung |
, | PUNCT | O |
insbesondere | ADV | O |
Bereitstellung | NOUN | B-Auslagerung |
der | DET | I-Auslagerung |
IT-Infrastruktur | NOUN | I-Auslagerung |
. | PUNCT | O |
Die | DET | O |
Gesellschaft | NOUN | O |
hat | AUX | O |
die | DET | O |
Funktion | NOUN | O |
der | DET | O |
Innenrevision | NOUN | B-Auslagerung |
, | PUNCT | I-Auslagerung |
die | DET | O |
Aufgaben | NOUN | O |
der | DET | O |
CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction
This inofficial dataset repository provides a CoNLL-like version of the CO-Fun NER dataset, that was proposed in the CO-Fun paper (https://arxiv.org/abs/2403.15322):
The process of cyber mapping gives insights in relationships among financial entities and service providers. Centered around the outsourcing practices of companies within fund prospectuses in Germany, we introduce a dataset specifically designed for named entity recognition and relation extraction tasks. The labeling process on 948 sentences was carried out by three experts which yields to 5,969 annotations for four entity types (Outsourcing, Company, Location and Software) and 4,102 relation annotations (Outsourcing-Company, Company-Location). State-of-the-art deep learning models were trained to recognize entities and extract relations showing first promising results.
Preprocessing
The notebook Export-To-CoNLL.ipynb performs the necessary steps to create a CoNLL-like version of the CO-Fun dataset, that could easily be used for fine-tuning NER models.
Additionally, the FlairDatasetTest.ipynb notebooks loads the dataset with the Flair dataset loader and checks, if the number of parsed sentences is correct and identical to the number of sentences reported in the official CO-Fun paper.
Named Entites
The CO-Fun dataset provides annotations for the following Named Entities:
Auslagerung
(engl. outsourcing)Unternehmen
(engl. company)Ort
(engl. location)Software
Example: Load Dataset with Flair library
The notebooks FlairDatasetExample.ipynb shows how to load the dataset with the awesome Flair library.
Changelog
- 25.03.2024: Initial version of the preprocessed CO-Fun NER dataset is released.
Licence
The original CO-Fun dataset is released under MIT license. Thus, this preprocessed version is also licenced under MIT.
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