{"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/learning-global-features-for-coreference","title":"Learning Global Features for Coreference Resolution","arxiv_id":"1604.03035","date":"2016-04-11","proceeding":"NAACL 2016 6","authors":["Sam Wiseman","Alexander M. Rush","Stuart M. Shieber"],"abstract":"There is compelling evidence that coreference prediction would benefit from\nmodeling global information about entity-clusters. Yet, state-of-the-art\nperformance can be achieved with systems treating each mention prediction\nindependently, which we attribute to the inherent difficulty of crafting\ninformative cluster-level features. We instead propose to use recurrent neural\nnetworks (RNNs) to learn latent, global representations of entity clusters\ndirectly from their mentions. We show that such representations are especially\nuseful for the prediction of pronominal mentions, and can be incorporated into\nan end-to-end coreference system that outperforms the state of the art without\nrequiring any additional search.","url_abs":"http://arxiv.org/abs/1604.03035v1","url_pdf":"http://arxiv.org/pdf/1604.03035v1.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":"learning-global-features-for-coreference","repo_url":"https://github.com/swiseman/nn_coref","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"torch","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"},{"task_slug":"coreference-resolution","task_name":"Coreference Resolution"},{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"coreference-resolution-1","task_name":"coreference-resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/coreference-resolution-on-ontonotes","task":"Coreference Resolution","dataset":"OntoNotes","model":"Global","rank_in_archive_order":26,"of":26,"metrics":{"F1":"64.21"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1604.03035","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}