README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - en
license:
  - cc-by-nc-sa-3.0
multilinguality:
  - monolingual
size_categories:
  - 10M<n<100M
source_datasets:
  - extended|natural_questions
task_categories:
  - multiple-choice
task_ids:
  - multiple-choice-qa
paperswithcode_id: asnq
pretty_name: Answer Sentence Natural Questions (ASNQ)
dataset_info:
  features:
    - name: question
      dtype: string
    - name: sentence
      dtype: string
    - name: label
      dtype:
        class_label:
          names:
            '0': neg
            '1': pos
    - name: sentence_in_long_answer
      dtype: bool
    - name: short_answer_in_sentence
      dtype: bool
  splits:
    - name: train
      num_bytes: 3656881376
      num_examples: 20377568
    - name: validation
      num_bytes: 168005155
      num_examples: 930062
  download_size: 3563857920
  dataset_size: 3824886531

Dataset Card for "asnq"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://github.com/alexa/wqa_tanda#answer-sentence-natural-questions-asnq
• Repository: More Information Needed
• Paper: TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 3398.76 MB
• Size of the generated dataset: 3647.70 MB
• Total amount of disk used: 7046.46 MB

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.