{"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/dgcn-based-solution-for-entity-linking-on","title":"DGCN Based Solution for Entity Linking on Visual Rich Document","arxiv_id":null,"date":"2022-11-16","proceeding":"no publication 2022 11","authors":["Shaodong Hou"],"abstract":"Various works on entity extraction on visual rich document (VRD) have been done. However, few methods have been explored to handle entity linking problem. The difficulties come from the number of possible linking edges among entities is of square times complexity. Our approach introduces directed graph based convolutional network (DGCN) to predict relations between entities, which out performs existing methods on the FUNSD entity linking task.","url_abs":"https://drive.google.com/file/d/1AwKBUkzkh4YwEADDofTJe-oIQbn-yIA6/view","url_pdf":"https://drive.google.com/file/d/1AwKBUkzkh4YwEADDofTJe-oIQbn-yIA6/view","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":"entity-linking","task_name":"Entity Linking"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/entity-linking-on-funsd","task":"Entity Linking","dataset":"FUNSD","model":"SINGU_GROUP","rank_in_archive_order":5,"of":7,"metrics":{"F1":"70.51"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}