{"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/harvesting-paragraph-level-question-answer","title":"Harvesting Paragraph-Level Question-Answer Pairs from Wikipedia","arxiv_id":"1805.05942","date":"2018-05-15","proceeding":"ACL 2018 7","authors":["Xinya Du","Claire Cardie"],"abstract":"We study the task of generating from Wikipedia articles question-answer pairs\nthat cover content beyond a single sentence. We propose a neural network\napproach that incorporates coreference knowledge via a novel gating mechanism.\nCompared to models that only take into account sentence-level information\n(Heilman and Smith, 2010; Du et al., 2017; Zhou et al., 2017), we find that the\nlinguistic knowledge introduced by the coreference representation aids question\ngeneration significantly, producing models that outperform the current\nstate-of-the-art. We apply our system (composed of an answer span extraction\nsystem and the passage-level QG system) to the 10,000 top-ranking Wikipedia\narticles and create a corpus of over one million question-answer pairs. We also\nprovide a qualitative analysis for this large-scale generated corpus from\nWikipedia.","url_abs":"http://arxiv.org/abs/1805.05942v1","url_pdf":"http://arxiv.org/pdf/1805.05942v1.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":"harvesting-paragraph-level-question-answer","repo_url":"https://github.com/xinyadu/harvestingQA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"articles","task_name":"Articles"},{"task_slug":"question-generation","task_name":"Question Generation"},{"task_slug":"question-generation","task_name":"Question-Generation"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.05942","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}