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Error code: FeaturesError Exception: ValueError Message: Not able to read records in the JSON file at hf://datasets/NYTK/HuCOLA@907b92006761244648449ffa55d88ce42942d793/data/cola_train.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['data']. Select the correct one and provide it as `field='XXX'` to the dataset loading method. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 240, 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 2216, 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 1239, 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 1389, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__ yield from islice(self.ex_iterable, self.n) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__ for key, pa_table in self.generate_tables_fn(**self.kwargs): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 170, in _generate_tables raise ValueError( ValueError: Not able to read records in the JSON file at hf://datasets/NYTK/HuCOLA@907b92006761244648449ffa55d88ce42942d793/data/cola_train.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['data']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.
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Dataset Card for HuCOLA
Dataset Summary
This is the dataset card for the Hungarian Corpus of Linguistic Acceptability (HuCOLA), which is also part of the Hungarian Language Understanding Evaluation Benchmark Kit HuLU.
Supported Tasks and Leaderboards
Languages
The BCP-47 code for Hungarian, the only represented language in this dataset, is hu-HU.
Dataset Structure
Data Instances
For each instance, there is aN id, a sentence and a label.
An example:
{"Sent_id": "dev_0",
"Sent": "A földek eláradtak.",
"Label": "0"}
Data Fields
- Sent_id: unique id of the instances, an integer between 1 and 1000;
- Sent: a Hungarian sentence;
- label: '0' for wrong, '1' for good sentences.
Data Splits
HuCOLA has 3 splits: train, validation and test.
Dataset split | Number of sentences in the split | Proportion of the split |
---|---|---|
train | 7276 | 80% |
validation | 900 | 10% |
test | 900 | 10% |
The test data is distributed without the labels. To evaluate your model, please contact us, or check HuLU's website for an automatic evaluation (this feature is under construction at the moment). The evaluation metric is Matthew's correlation coefficient.
Dataset Creation
Source Data
Initial Data Collection and Normalization
The data was collected by two human annotators from 3 main linguistic books on Hungarian language:
- Kiefer Ferenc (ed.) (1992), Strukturális magyar nyelvtan 1. Mondattan. Budapest, Akadémiai Kiadó.
- Alberti, Gábor and Laczkó, Tibor (eds) (2018), Syntax of Hungarian Nouns and Noun Phrases. I., II. Comprehensive grammar resources. Amsterdam University Press, Amsterdam.
- Katalin É. Kiss and Veronika Hegedűs (eds) (2021), Postpositions and Postpositional Phrases. Amsterdam: Amsterdam University Press.
The process of collecting sentences partly followed the one described in Warstadt et. al (2018). The guideline of our process is available in the repository of HuCOLA.
Annotations
Annotation process
Each instance was annotated by 4 human annotators for its acceptability (see the annotation guidelines in the repository of HuCOLA).
Who are the annotators?
The annotators were native Hungarian speakers (of various ages, from 20 to 67) without any linguistic backround.
Additional Information
Licensing Information
HuCOLA is released under the CC-BY-SA 4.0 licence.
Citation Information
If you use this resource or any part of its documentation, please refer to:
Ligeti-Nagy, N., Ferenczi, G., Héja, E., Jelencsik-Mátyus, K., Laki, L. J., Vadász, N., Yang, Z. Gy. and Váradi, T. (2022) HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából [HuLU: Hungarian benchmark dataset to evaluate neural language models]. XVIII. Magyar Számítógépes Nyelvészeti Konferencia. (in press)
@inproceedings{ligetinagy2022hulu,
title={HuLU: magyar nyelvű benchmark adatbázis kiépítése a neurális nyelvmodellek kiértékelése céljából},
author={Ligeti-Nagy, N. and Ferenczi, G. and Héja, E. and Jelencsik-Mátyus, K. and Laki, L. J. and Vadász, N. and Yang, Z. Gy. and Váradi, T.},
booktitle={XVIII. Magyar Számítógépes Nyelvészeti Konferencia},
year={2022}
}
Contributions
Thanks to lnnoemi for adding this dataset.
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