lmqg/qag_squad

这是一个基于SQuAD的问题与答案生成数据集，主要用于训练模型进行问题与答案的生成。数据集包含段落、问题、答案以及问题和答案的组合字段。所有数据分割（训练、验证、测试）的结构一致。数据集支持英语，并用于评估模型在生成问题与答案时的性能，通常通过BLEU4、METEOR、ROUGE-L、BERTScore和MoverScore等指标来衡量。

This is a question and answer generation dataset based on SQuAD, primarily used for training models to generate questions and answers. The dataset contains fields including paragraphs, questions, answers, and combined question-answer pairs. All data splits (training, validation, and test) share consistent structures. This dataset supports English and is designed to evaluate models' performance in question and answer generation, which is typically measured using metrics such as BLEU4, METEOR, ROUGE-L, BERTScore, and MoverScore.

原始信息汇总

数据集概述

基本信息

• 许可证: cc-by-sa-4.0
• 数据集名称: SQuAD for question generation
• 语言: 英语 (en)
• 多语言性: 单语种
• 数据集大小: 1k<n<10K
• 来源数据集: lmqg/qg_squad

任务与标签

• 任务类别: 文本生成
• 任务ID: 语言建模
• 标签: 问题生成

数据集描述

• 数据集摘要: 基于SQuAD的问题与答案生成数据集。
• 支持的任务与评测指标:
  • 任务: 问题答案生成
  • 评测指标: BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore

数据集结构

• 数据字段:
  • questions: 字符串列表
  • answers: 字符串列表
  • paragraph: 字符串
  • questions_answers: 字符串

数据分割

分割	样本数
train	16462
validation	2067
test	2429

引用信息

@inproceedings{ushio-etal-2022-generative, title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration", author = "Ushio, Asahi and Alva-Manchego, Fernando and Camacho-Collados, Jose", booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing", month = dec, year = "2022", address = "Abu Dhabi, U.A.E.", publisher = "Association for Computational Linguistics", }