{"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/heterogeneous-supervision-for-relation","title":"Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach","arxiv_id":"1707.00166","date":"2017-07-01","proceeding":"EMNLP 2017 9","authors":["Liyuan Liu","Xiang Ren","Qi Zhu","Shi Zhi","Huan Gui","Heng Ji","Jiawei Han"],"abstract":"Relation extraction is a fundamental task in information extraction. Most\nexisting methods have heavy reliance on annotations labeled by human experts,\nwhich are costly and time-consuming. To overcome this drawback, we propose a\nnovel framework, REHession, to conduct relation extractor learning using\nannotations from heterogeneous information source, e.g., knowledge base and\ndomain heuristics. These annotations, referred as heterogeneous supervision,\noften conflict with each other, which brings a new challenge to the original\nrelation extraction task: how to infer the true label from noisy labels for a\ngiven instance. Identifying context information as the backbone of both\nrelation extraction and true label discovery, we adopt embedding techniques to\nlearn the distributed representations of context, which bridges all components\nwith mutual enhancement in an iterative fashion. Extensive experimental results\ndemonstrate the superiority of REHession over the state-of-the-art.","url_abs":"http://arxiv.org/abs/1707.00166v2","url_pdf":"http://arxiv.org/pdf/1707.00166v2.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":"heterogeneous-supervision-for-relation","repo_url":"https://github.com/LiyuanLucasLiu/ReHession","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":null,"task_name":"Relation"},{"task_slug":"relation-extraction","task_name":"Relation Extraction"},{"task_slug":"representation-learning","task_name":"Representation Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1707.00166","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}