lmqg/qag_esquad

这是一个基于ESQuAD的问答生成数据集，主要用于训练问答生成模型。数据集包含段落、问题、答案以及问题和答案的组合字段。数据为西班牙语，且数据结构在所有分割中保持一致。数据集的任务成功通常通过BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore等指标来衡量。

This is a question answering generation dataset built upon ESQuAD, primarily intended for training QA generation models. The dataset includes fields such as paragraphs, questions, answers, and combined question-answer pairs. All data is in Spanish, and the data structure remains consistent across all dataset splits. The task performance of this dataset is typically evaluated using metrics including BLEU4, METEOR, ROUGE-L, BERTScore, and MoverScore.

原始信息汇总

数据集概述

数据集描述

• 名称: SQuAD for question generation
• 语言: 西班牙语 (es)
• 许可: cc-by-sa-4.0
• 规模: 1k<n<10K
• 来源: lmqg/qg_esquad
• 任务类别:
  • text-generation
• 任务ID:
  • language-modeling
• 标签:
  • question-generation

数据集总结

这是一个基于ESQuAD的问答生成数据集。

支持的任务和排行榜

• 任务: 问答生成
• 成功指标: BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore

数据集结构

• 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	18829
validation	2067
test	8234

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", }

搜集汇总

背景与挑战

背景概述

这是一个西班牙语的问答生成数据集，基于ESQuAD构建，用于训练问答生成模型。数据集包含段落、问题、答案及其组合字段，数据结构一致，通常使用BLEU4、METEOR等指标评估任务成功。