Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
question-generation
License:
metadata
license: cc-by-4-0
pretty_name: SQuAD QG
languages: en
multilinguality: monolingual
size_categories: 10K<n<100K
source_datasets: extended|wikipedia
task_categories: question-generation
task_ids: question-generation
Dataset Card for "qg_squad"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Repository: https://github.com/asahi417/lm-question-generation
- Paper: More Information Needed
- Point of Contact: Asahi Ushio
- Size of downloaded dataset files: 284.1 MB
- Size of the generated dataset: 269 MB
Dataset Summary
SQuAD dataset for question generation (QG) task. The split of train/development/test set follows the "Neural Question Generation" work and is compatible with the leader board.
Supported Tasks and Leaderboards
question-generation
: The dataset can be used to train a model for question generation. Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L score. This task has an active leaderboard which can be found at here.
Languages
English (en)
Dataset Structure
Data Instances
plain_text
- Size of downloaded dataset files: 284.1 MB
- Size of the generated dataset: 269 MB An example of 'train' looks as follows.
{
"question": "What is heresy mainly at odds with?",
"paragraph": "Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs. A heretic is a proponent of such claims or beliefs. Heresy is distinct from both apostasy, which is the explicit renunciation of one's religion, principles or cause, and blasphemy, which is an impious utterance or action concerning God or sacred things.",
"answer": "established beliefs or customs",
"sentence": "Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs .",
"paragraph_sentence": "<hl> Heresy is any provocative belief or theory that is strongly at variance with established beliefs or customs . <hl> A heretic is a proponent of such claims or beliefs. Heresy is distinct from both apostasy, which is the explicit renunciation of one's religion, principles or cause, and blasphemy, which is an impious utterance or action concerning God or sacred things.",
"paragraph_answer": "Heresy is any provocative belief or theory that is strongly at variance with <hl> established beliefs or customs <hl>. A heretic is a proponent of such claims or beliefs. Heresy is distinct from both apostasy, which is the explicit renunciation of one's religion, principles or cause, and blasphemy, which is an impious utterance or action concerning God or sacred things.",
"sentence_answer": "Heresy is any provocative belief or theory that is strongly at variance with <hl> established beliefs or customs <hl> ."
}
Data Fields
The data fields are the same among all splits.
plain_text
question
: astring
feature.paragraph
: astring
feature.answer
: astring
feature.sentence
: astring
feature.paragraph_answer
: astring
feature, which is same as the paragraph but the answer is highlighted by a special token<hl>
.paragraph_sentence
: astring
feature, which is same as the paragraph but a sentence containing the answer is highlighted by a special token<hl>
.sentence_answer
: astring
feature, which is same as the sentence but the answer is highlighted by a special token<hl>
.
Each of paragraph_answer
, paragraph_sentence
, and sentence_answer
feature is assumed to be used to train a question generation model,
but with different information. The paragraph_answer
and sentence_answer
features are for answer-aware question generation and
paragraph_sentence
feature is for sentence-aware question generation.
Data Splits
name | train | validation | test |
---|---|---|---|
plain_text | 75722 | 10570 | 11877 |