{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/dureader-a-chinese-machine-reading","title":"DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications","arxiv_id":"1711.05073","date":"2017-11-14","proceeding":"WS 2018 7","authors":["Wei He","Kai Liu","Jing Liu","Yajuan Lyu","Shiqi Zhao","Xinyan Xiao","Yu-An Liu","Yizhong Wang","Hua Wu","Qiaoqiao She","Xuan Liu","Tian Wu","Haifeng Wang"],"abstract":"This paper introduces DuReader, a new large-scale, open-domain Chinese ma-\nchine reading comprehension (MRC) dataset, designed to address real-world MRC.\nDuReader has three advantages over previous MRC datasets: (1) data sources:\nquestions and documents are based on Baidu Search and Baidu Zhidao; answers are\nmanually generated. (2) question types: it provides rich annotations for more\nquestion types, especially yes-no and opinion questions, that leaves more\nopportunity for the research community. (3) scale: it contains 200K questions,\n420K answers and 1M documents; it is the largest Chinese MRC dataset so far.\nExperiments show that human performance is well above current state-of-the-art\nbaseline systems, leaving plenty of room for the community to make\nimprovements. To help the community make these improvements, both DuReader and\nbaseline systems have been posted online. We also organize a shared competition\nto encourage the exploration of more models. Since the release of the task,\nthere are significant improvements over the baselines.","url_abs":"http://arxiv.org/abs/1711.05073v4","url_pdf":"http://arxiv.org/pdf/1711.05073v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"dureader-a-chinese-machine-reading","repo_url":"https://github.com/PaddlePaddle/models","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"paddle","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"dureader-a-chinese-machine-reading","repo_url":"https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/machine_reading_comprehension/DuReader-robust","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":null},{"paper_slug":"dureader-a-chinese-machine-reading","repo_url":"https://github.com/PaddlePaddle/PaddleNLP/tree/develop/examples/machine_reading_comprehension/DuReader-yesno","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":null}],"tasks":[{"task_slug":"machine-reading-comprehension","task_name":"Machine Reading Comprehension"},{"task_slug":"reading-comprehension","task_name":"Reading Comprehension"}],"methods":[],"datasets_introduced":[{"slug":"dureader","name":"DuReader","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1711.05073","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}