{"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/chemu-ref-a-corpus-for-modeling-anaphora","title":"ChEMU-Ref: A Corpus for Modeling Anaphora Resolution in the Chemical Domain","arxiv_id":null,"date":"2021-04-01","proceeding":"EACL 2021 2","authors":["Biaoyan Fang","Christian Druckenbrodt","Saber A Akhondi","Jiayuan He","Timothy Baldwin","Karin Verspoor"],"abstract":"Chemical patents contain rich coreference and bridging links, which are the target of this research. Specially, we introduce a novel annotation scheme, based on which we create the ChEMU-Ref dataset from reaction description snippets in English-language chemical patents. We propose a neural approach to anaphora resolution, which we show to achieve strong results, especially when jointly trained over coreference and bridging links.","url_abs":"https://aclanthology.org/2021.eacl-main.116","url_pdf":"https://aclanthology.org/2021.eacl-main.116.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":"chemu-ref-a-corpus-for-modeling-anaphora","repo_url":"https://github.com/biaoyanf/chemu-ref","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}