{"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/semantic-framework-based-query-generation-for","title":"Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs","arxiv_id":"2210.04490","date":"2022-10-10","proceeding":null,"authors":["Wentao Ding","Hao Chen","Huayu Li","Yuzhong Qu"],"abstract":"Answering factual questions with temporal intent over knowledge graphs (temporal KGQA) attracts rising attention in recent years. In the generation of temporal queries, existing KGQA methods ignore the fact that some intrinsic connections between events can make them temporally related, which may limit their capability. We systematically analyze the possible interpretation of temporal constraints and conclude the interpretation structures as the Semantic Framework of Temporal Constraints, SF-TCons. Based on the semantic framework, we propose a temporal question answering method, SF-TQA, which generates query graphs by exploring the relevant facts of mentioned entities, where the exploring process is restricted by SF-TCons. Our evaluations show that SF-TQA significantly outperforms existing methods on two benchmarks over different knowledge graphs.","url_abs":"https://arxiv.org/abs/2210.04490v3","url_pdf":"https://arxiv.org/pdf/2210.04490v3.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":[],"tasks":[{"task_slug":"knowledge-graphs","task_name":"Knowledge Graphs"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/question-answering-on-tempquestions","task":"Question Answering","dataset":"TempQuestions","model":"SF-TQA","rank_in_archive_order":1,"of":8,"metrics":{"F1":"41.1","Hits@1":"41.2"},"uses_additional_data":false},{"leaderboard":"/sota/question-answering-on-timequestions","task":"Question Answering","dataset":"TimeQuestions","model":"SF-TQA","rank_in_archive_order":5,"of":21,"metrics":{"P@1":"53.9"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2210.04490","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}