{"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/fewrel-a-large-scale-supervised-few-shot","title":"FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation","arxiv_id":"1810.10147","date":"2018-10-24","proceeding":"EMNLP 2018 10","authors":["Xu Han","Hao Zhu","Pengfei Yu","ZiYun Wang","Yuan YAO","Zhiyuan Liu","Maosong Sun"],"abstract":"We present a Few-Shot Relation Classification Dataset (FewRel), consisting of\n70, 000 sentences on 100 relations derived from Wikipedia and annotated by\ncrowdworkers. The relation of each sentence is first recognized by distant\nsupervision methods, and then filtered by crowdworkers. We adapt the most\nrecent state-of-the-art few-shot learning methods for relation classification\nand conduct a thorough evaluation of these methods. Empirical results show that\neven the most competitive few-shot learning models struggle on this task,\nespecially as compared with humans. We also show that a range of different\nreasoning skills are needed to solve our task. These results indicate that\nfew-shot relation classification remains an open problem and still requires\nfurther research. Our detailed analysis points multiple directions for future\nresearch. All details and resources about the dataset and baselines are\nreleased on http://zhuhao.me/fewrel.","url_abs":"http://arxiv.org/abs/1810.10147v2","url_pdf":"http://arxiv.org/pdf/1810.10147v2.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":"fewrel-a-large-scale-supervised-few-shot","repo_url":"https://github.com/ProKil/FewRel","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"few-shot-learning","task_name":"Few-Shot Learning"},{"task_slug":"few-shot-relation-classification","task_name":"Few-Shot Relation Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":null,"task_name":"Relation"},{"task_slug":"relation-classification","task_name":"Relation Classification"},{"task_slug":"relation-extraction","task_name":"Relation Extraction"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[{"slug":"fewrel","name":"FewRel","full_name":"Few-Shot Relation Classification Dataset"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1810.10147","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.10147"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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