{"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/streamlining-cross-document-coreference","title":"Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling","arxiv_id":"2009.11032","date":"2020-09-23","proceeding":null,"authors":["Arie Cattan","Alon Eirew","Gabriel Stanovsky","Mandar Joshi","Ido Dagan"],"abstract":"Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation of performance. To facilitate proper future research on this task, our primary contribution is proposing a pragmatic evaluation methodology which assumes access to only raw text -- rather than assuming gold mentions, disregards singleton prediction, and addresses typical targeted settings in CD coreference resolution. Aiming to set baseline results for future research that would follow our evaluation methodology, we build the first end-to-end model for this task. Our model adapts and extends recent neural models for within-document coreference resolution to address the CD coreference setting, which outperforms state-of-the-art results by a significant margin.","url_abs":"https://arxiv.org/abs/2009.11032v3","url_pdf":"https://arxiv.org/pdf/2009.11032v3.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":"streamlining-cross-document-coreference","repo_url":"https://github.com/ariecattan/coref","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"streamlining-cross-document-coreference","repo_url":"https://github.com/ariecattan/SciCo","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"coreference-resolution","task_name":"Coreference Resolution"},{"task_slug":"cross-document-coreference-resolution","task_name":"Cross Document Coreference Resolution"},{"task_slug":"entity-cross-document-coreference-resolution","task_name":"Entity Cross-Document Coreference Resolution"},{"task_slug":"event-cross-document-coreference-resolution","task_name":"Event Cross-Document Coreference Resolution"},{"task_slug":"coreference-resolution-1","task_name":"coreference-resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2009.11032","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}