Datasets:

sonquoctran
/

SQuAD_AGent

ArXiv:

Dataset Viewer

Split (2)

train

The dataset viewer is not available for this split.

Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.

Error code:   FeaturesError
Exception:    ValueError
Message:      Not able to read records in the JSON file at hf://datasets/sonquoctran/SQuAD_AGent@ad802cdcad76b2869a297d914ccdd6b94d1b46eb/SQuAD_AGent_train.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['version', '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/sonquoctran/SQuAD_AGent@ad802cdcad76b2869a297d914ccdd6b94d1b46eb/SQuAD_AGent_train.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['version', 'data']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.

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YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

AGent: A Novel Pipeline for Automatically Creating Unanswerable Questions

Introduction

AGent: A Novel Pipeline for Automatically Creating Unanswerable Questions
Son Quoc Tran, Gia-Huy Do, Phong Nguyen-Thuan Do, Matt Kretchmar, Xinya Du
Computer Science Department, Denison University, Granville, Ohio
The UIT NLP Group, Vietnam National University, Ho Chi Minh City
University of Texas at Dallas

AGent

Agent pipeline has three steps:
1. Matching questions with new contexts.
2. Identifying hard unanswerable questions.
3. Filtering out answerable questions.

Citation and Contact

If you found this repository helpful, please cite:

@misc{tran2023agent,
      title={AGent: A Novel Pipeline for Automatically Creating Unanswerable Questions}, 
      author={Son Quoc Tran and Gia-Huy Do and Phong Nguyen-Thuan Do and Matt Kretchmar and Xinya Du},
      year={2023},
      eprint={2309.05103},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Please contact Son Quoc Tran at [email protected] if you have any questions.

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