{"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/resolving-event-coreference-with-supervised","title":"Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization","arxiv_id":"1805.10985","date":"2018-05-28","proceeding":"SEMEVAL 2018 6","authors":["Kian Kenyon-Dean","Jackie Chi Kit Cheung","Doina Precup"],"abstract":"We present an approach to event coreference resolution by developing a\ngeneral framework for clustering that uses supervised representation learning.\nWe propose a neural network architecture with novel Clustering-Oriented\nRegularization (CORE) terms in the objective function. These terms encourage\nthe model to create embeddings of event mentions that are amenable to\nclustering. We then use agglomerative clustering on these embeddings to build\nevent coreference chains. For both within- and cross-document coreference on\nthe ECB+ corpus, our model obtains better results than models that require\nsignificantly more pre-annotated information. This work provides insight and\nmotivating results for a new general approach to solving coreference and\nclustering problems with representation learning.","url_abs":"http://arxiv.org/abs/1805.10985v1","url_pdf":"http://arxiv.org/pdf/1805.10985v1.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":"resolving-event-coreference-with-supervised","repo_url":"https://github.com/kiankd/events","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"coreference-resolution","task_name":"Coreference Resolution"},{"task_slug":"event-coreference-resolution","task_name":"Event Coreference Resolution"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"coreference-resolution-1","task_name":"coreference-resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.10985","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}