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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    NotImplementedError
Message:      Extraction protocol for TAR archives like 'https://wqa-public.s3.amazonaws.com/tanda-aaai-2020/data/asnq.tar' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.

Example usage:

	url = dl_manager.download(url)
	tar_archive_iterator = dl_manager.iter_archive(url)

	for filename, file in tar_archive_iterator:
		...
Traceback:    Traceback (most recent call last):
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 485, in compute_first_rows_response
                  rows = get_rows(
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 120, in decorator
                  return func(*args, **kwargs)
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 164, in get_rows
                  ds = load_dataset(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/load.py", line 1751, in load_dataset
                  return builder_instance.as_streaming_dataset(split=split)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1206, in as_streaming_dataset
                  splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
                File "/tmp/modules-cache/datasets_modules/datasets/asnq/9d1e778b346e77ce06267638bbcb8745661548238317f5ebf8c821d530ac9fad/asnq.py", line 101, in _split_generators
                  dl_dir = dl_manager.download_and_extract(_URL)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1074, in download_and_extract
                  return self.extract(self.download(url_or_urls))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1026, in extract
                  urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 436, in map_nested
                  return function(data_struct)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1036, in _extract
                  raise NotImplementedError(
              NotImplementedError: Extraction protocol for TAR archives like 'https://wqa-public.s3.amazonaws.com/tanda-aaai-2020/data/asnq.tar' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.
              
              Example usage:
              
              	url = dl_manager.download(url)
              	tar_archive_iterator = dl_manager.iter_archive(url)
              
              	for filename, file in tar_archive_iterator:
              		...

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Dataset Card for "asnq"

Dataset Summary

ASNQ is a dataset for answer sentence selection derived from Google's Natural Questions (NQ) dataset (Kwiatkowski et al. 2019).

Each example contains a question, candidate sentence, label indicating whether or not the sentence answers the question, and two additional features -- sentence_in_long_answer and short_answer_in_sentence indicating whether ot not the candidate sentence is contained in the long_answer and if the short_answer is in the candidate sentence.

For more details please see https://arxiv.org/abs/1911.04118

and

https://research.google/pubs/pub47761/

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

  • Size of downloaded dataset files: 3398.76 MB
  • Size of the generated dataset: 3647.70 MB
  • Total amount of disk used: 7046.46 MB

An example of 'validation' looks as follows.

{
    "label": 0,
    "question": "when did somewhere over the rainbow come out",
    "sentence": "In films and TV shows ( edit ) In the film Third Finger , Left Hand ( 1940 ) with Myrna Loy , Melvyn Douglas , and Raymond Walburn , the tune played throughout the film in short sequences .",
    "sentence_in_long_answer": false,
    "short_answer_in_sentence": false
}

Data Fields

The data fields are the same among all splits.

default

  • question: a string feature.
  • sentence: a string feature.
  • label: a classification label, with possible values including neg (0), pos (1).
  • sentence_in_long_answer: a bool feature.
  • short_answer_in_sentence: a bool feature.

Data Splits

name train validation
default 20377568 930062

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

The data is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License: https://github.com/alexa/wqa_tanda/blob/master/LICENSE

Citation Information

@article{Garg_2020,
   title={TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection},
   volume={34},
   ISSN={2159-5399},
   url={http://dx.doi.org/10.1609/AAAI.V34I05.6282},
   DOI={10.1609/aaai.v34i05.6282},
   number={05},
   journal={Proceedings of the AAAI Conference on Artificial Intelligence},
   publisher={Association for the Advancement of Artificial Intelligence (AAAI)},
   author={Garg, Siddhant and Vu, Thuy and Moschitti, Alessandro},
   year={2020},
   month={Apr},
   pages={7780–7788}
}

Contributions

Thanks to @mkserge for adding this dataset.

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