{"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/mixing-context-granularities-for-improved","title":"Mixing Context Granularities for Improved Entity Linking on Question Answering Data across Entity Categories","arxiv_id":"1804.08460","date":"2018-04-23","proceeding":"SEMEVAL 2018 6","authors":["Daniil Sorokin","Iryna Gurevych"],"abstract":"The first stage of every knowledge base question answering approach is to\nlink entities in the input question. We investigate entity linking in the\ncontext of a question answering task and present a jointly optimized neural\narchitecture for entity mention detection and entity disambiguation that models\nthe surrounding context on different levels of granularity. We use the Wikidata\nknowledge base and available question answering datasets to create benchmarks\nfor entity linking on question answering data. Our approach outperforms the\nprevious state-of-the-art system on this data, resulting in an average 8%\nimprovement of the final score. We further demonstrate that our model delivers\na strong performance across different entity categories.","url_abs":"http://arxiv.org/abs/1804.08460v1","url_pdf":"http://arxiv.org/pdf/1804.08460v1.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":"mixing-context-granularities-for-improved","repo_url":"https://github.com/UKPLab/starsem2018-entity-linking","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"entity-disambiguation","task_name":"Entity Disambiguation"},{"task_slug":"entity-linking","task_name":"Entity Linking"},{"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/entity-linking-on-webqsp-wd","task":"Entity Linking","dataset":"WebQSP-WD","model":"VCG","rank_in_archive_order":2,"of":2,"metrics":{"F1":"0.73"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.08460","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}