{"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/deep-joint-entity-disambiguation-with-local","title":"Deep Joint Entity Disambiguation with Local Neural Attention","arxiv_id":"1704.04920","date":"2017-04-17","proceeding":"EMNLP 2017 9","authors":["Octavian-Eugen Ganea","Thomas Hofmann"],"abstract":"We propose a novel deep learning model for joint document-level entity\ndisambiguation, which leverages learned neural representations. Key components\nare entity embeddings, a neural attention mechanism over local context windows,\nand a differentiable joint inference stage for disambiguation. Our approach\nthereby combines benefits of deep learning with more traditional approaches\nsuch as graphical models and probabilistic mention-entity maps. Extensive\nexperiments show that we are able to obtain competitive or state-of-the-art\naccuracy at moderate computational costs.","url_abs":"http://arxiv.org/abs/1704.04920v3","url_pdf":"http://arxiv.org/pdf/1704.04920v3.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":"deep-joint-entity-disambiguation-with-local","repo_url":"https://github.com/dalab/deep-ed","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"torch","reach":{"status":"unanswered"}},{"paper_slug":"deep-joint-entity-disambiguation-with-local","repo_url":"https://github.com/klimzaporojets/DWIE","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"deep-joint-entity-disambiguation-with-local","repo_url":"https://github.com/yifding/deep_ed_PyTorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"entity-disambiguation","task_name":"Entity Disambiguation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/entity-disambiguation-on-ace2004","task":"Entity Disambiguation","dataset":"ACE2004","model":"Global","rank_in_archive_order":6,"of":6,"metrics":{"Micro-F1":"88.5"},"uses_additional_data":false},{"leaderboard":"/sota/entity-disambiguation-on-aida-conll","task":"Entity Disambiguation","dataset":"AIDA-CoNLL","model":"Global","rank_in_archive_order":14,"of":20,"metrics":{"In-KB Accuracy":"92.22"},"uses_additional_data":false},{"leaderboard":"/sota/entity-disambiguation-on-aquaint","task":"Entity Disambiguation","dataset":"AQUAINT","model":"Global","rank_in_archive_order":5,"of":6,"metrics":{"Micro-F1":"88.5"},"uses_additional_data":false},{"leaderboard":"/sota/entity-disambiguation-on-msnbc","task":"Entity Disambiguation","dataset":"MSNBC","model":"Global","rank_in_archive_order":5,"of":6,"metrics":{"Micro-F1":"93.7"},"uses_additional_data":false},{"leaderboard":"/sota/entity-disambiguation-on-wned-cweb","task":"Entity Disambiguation","dataset":"WNED-CWEB","model":"Global","rank_in_archive_order":4,"of":7,"metrics":{"Micro-F1":"77.9"},"uses_additional_data":false},{"leaderboard":"/sota/entity-disambiguation-on-wned-wiki","task":"Entity Disambiguation","dataset":"WNED-WIKI","model":"Glonal","rank_in_archive_order":6,"of":7,"metrics":{"Micro-F1":"77.5"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1704.04920","atlas_url":"https://app.syntology.ai/?focus=1704.04920","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}