{"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/joint-extraction-of-events-and-entities","title":"Joint Extraction of Events and Entities within a Document Context","arxiv_id":"1609.03632","date":"2016-09-12","proceeding":"NAACL 2016 6","authors":["Bishan Yang","Tom Mitchell"],"abstract":"Events and entities are closely related; entities are often actors or\nparticipants in events and events without entities are uncommon. The\ninterpretation of events and entities is highly contextually dependent.\nExisting work in information extraction typically models events separately from\nentities, and performs inference at the sentence level, ignoring the rest of\nthe document. In this paper, we propose a novel approach that models the\ndependencies among variables of events, entities, and their relations, and\nperforms joint inference of these variables across a document. The goal is to\nenable access to document-level contextual information and facilitate\ncontext-aware predictions. We demonstrate that our approach substantially\noutperforms the state-of-the-art methods for event extraction as well as a\nstrong baseline for entity extraction.","url_abs":"http://arxiv.org/abs/1609.03632v1","url_pdf":"http://arxiv.org/pdf/1609.03632v1.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":"joint-extraction-of-events-and-entities","repo_url":"https://github.com/bishanyang/EventEntityExtractor","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"entity-extraction","task_name":"Entity Extraction using GAN"},{"task_slug":"event-extraction","task_name":"Event Extraction"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1609.03632","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}