文献类型：会议论文

英文题名：MA-MRC: A Multi-answer Machine Reading Comprehension Dataset

作者：Yue, Zhiang[1];Liu, Jingping[2];Zhang, Cong[3];Wang, Chao[4];Jiang, Haiyun[5];Zhang, Yue[2];Tian, Xianyang[2];Cen, Zhedong[2];Xiao, Yanghua[1];Ruan, Tong[2]

机构：[1]Fudan Univ, Shanghai, Peoples R China;[2]East China Univ Sci & Technol, Shanghai, Peoples R China;[3]AECC Sichuan Gas Turbine Estab, Mianyang, Sichuan, Peoples R China;[4]Shanghai Univ, Shanghai, Peoples R China;[5]Tencent AI Lab, Shenzhen, Peoples R China

会议论文集：46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

会议日期：JUL 23-27, 2023

会议地点：Taipei, TAIWAN

语种：英文

外文关键词：Machine Reading Comprehension; Multiple Answer; Knowledge Graph

摘要：Machine reading comprehension (MRC) is an essential task for many question-answering applications. However, existing MRC datasets mainly focus on data with single answer and overlook multiple answers, which are common in the real world. In this paper, we aim to construct an MRC dataset with both data of single answer and multiple answers. To achieve this purpose, we design a novel pipeline method: data collection, data cleaning, question generation and test set annotation. Based on these procedures, we construct a high-quality multi-answer MRC dataset (MA-MRC) with 129K question-answer-context samples. We implement a sequence of baselines and carry out extensive experiments on MA-MRC. According to the experimental results, MA-MRC is a challenging dataset, which can facilitate the future research on the multi-answer MRC task(1).