{"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/using-linguistic-features-to-improve-the","title":"Using Linguistic Features to Improve the Generalization Capability of Neural Coreference Resolvers","arxiv_id":"1708.00160","date":"2017-08-01","proceeding":"EMNLP 2018 10","authors":["Nafise Sadat Moosavi","Michael Strube"],"abstract":"Coreference resolution is an intermediate step for text understanding. It is\nused in tasks and domains for which we do not necessarily have coreference\nannotated corpora. Therefore, generalization is of special importance for\ncoreference resolution. However, while recent coreference resolvers have\nnotable improvements on the CoNLL dataset, they struggle to generalize properly\nto new domains or datasets. In this paper, we investigate the role of\nlinguistic features in building more generalizable coreference resolvers. We\nshow that generalization improves only slightly by merely using a set of\nadditional linguistic features. However, employing features and subsets of\ntheir values that are informative for coreference resolution, considerably\nimproves generalization. Thanks to better generalization, our system achieves\nstate-of-the-art results in out-of-domain evaluations, e.g., on WikiCoref, our\nsystem, which is trained on CoNLL, achieves on-par performance with a system\ndesigned for this dataset.","url_abs":"http://arxiv.org/abs/1708.00160v2","url_pdf":"http://arxiv.org/pdf/1708.00160v2.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":"using-linguistic-features-to-improve-the","repo_url":"https://github.com/ns-moosavi/epm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"coreference-resolution","task_name":"Coreference Resolution"},{"task_slug":"coreference-resolution-1","task_name":"coreference-resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}