{"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/fcgec-fine-grained-corpus-for-chinese","title":"FCGEC: Fine-Grained Corpus for Chinese Grammatical Error Correction","arxiv_id":"2210.12364","date":"2022-10-22","proceeding":null,"authors":["Lvxiaowei Xu","Jianwang Wu","Jiawei Peng","Jiayu Fu","Ming Cai"],"abstract":"Grammatical Error Correction (GEC) has been broadly applied in automatic correction and proofreading system recently. However, it is still immature in Chinese GEC due to limited high-quality data from native speakers in terms of category and scale. In this paper, we present FCGEC, a fine-grained corpus to detect, identify and correct the grammatical errors. FCGEC is a human-annotated corpus with multiple references, consisting of 41,340 sentences collected mainly from multi-choice questions in public school Chinese examinations. Furthermore, we propose a Switch-Tagger-Generator (STG) baseline model to correct the grammatical errors in low-resource settings. Compared to other GEC benchmark models, experimental results illustrate that STG outperforms them on our FCGEC. However, there exists a significant gap between benchmark models and humans that encourages future models to bridge it.","url_abs":"https://arxiv.org/abs/2210.12364v1","url_pdf":"https://arxiv.org/pdf/2210.12364v1.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":"fcgec-fine-grained-corpus-for-chinese","repo_url":"https://github.com/xlxwalex/FCGEC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"fcgec-fine-grained-corpus-for-chinese","repo_url":"https://github.com/xlxwalex/hycxg","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"grammatical-error-correction","task_name":"Grammatical Error Correction"},{"task_slug":"grammatical-error-detection","task_name":"Grammatical Error Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/grammatical-error-correction-on-fcgec","task":"Grammatical Error Correction","dataset":"FCGEC","model":"STG-Joint","rank_in_archive_order":1,"of":1,"metrics":{"F0.5":"45.48","exact match":"34.10"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2210.12364","atlas_url":"https://app.syntology.ai/?focus=2210.12364","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}