{"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/edg-based-question-decomposition-for-complex","title":"EDG-Based Question Decomposition for Complex Question Answering over Knowledge Bases","arxiv_id":null,"date":"2021-10-24","proceeding":"ISWC 2021 10","authors":["Xixin Hu","Yiheng Shu","Xiang Huang","Yuzhong Qu"],"abstract":"Knowledge base question answering (KBQA) aims at automatically answering factoid questions over knowledge bases (KBs). For complex questions that require multiple KB relations or constraints, KBQA faces many challenges including question understanding, component linking (e.g., entity, relation, and type linking), and query composition. In this paper, we propose a novel graph structure called Entity Description Graph (EDG) to represent the structure of complex questions, which can help alleviate the above issues. By leveraging the EDG structure of given questions, we implement a QA system over DBpedia, called EDGQA. Extensive experiments demonstrate that EDGQA outperforms state-of-the-art results on both LC-QuAD and QALD-9, and that EDG-based decomposition is a feasible way for complex question answering over KBs.","url_abs":"https://dl.acm.org/doi/10.1007/978-3-030-88361-4_8","url_pdf":"https://dl.acm.org/doi/10.1007/978-3-030-88361-4_8","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":[],"tasks":[{"task_slug":"knowledge-base-question-answering","task_name":"Knowledge Base Question Answering"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/knowledge-base-question-answering-on-lc-quad","task":"Knowledge Base Question Answering","dataset":"LC-QuAD 1.0","model":"EDGQA","rank_in_archive_order":6,"of":7,"metrics":{"F1":"53.1"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}