{"type":"ScholarlyArticle","title":"NerCo: A Contrastive Learning Based Two-Stage Chinese NER Method","authors":[{"name":"Zai Zhang","slug":"zai-zhang","given":"Zai","family":"Zhang","affiliation":"School of Computer Science and Technology , Xi'an Jiaotong University , China; Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering , Xi'an Jiaotong University , China"},{"name":"Bin Shi","slug":"bin-shi","given":"Bin","family":"Shi","affiliation":"School of Computer Science and Technology , Xi'an Jiaotong University , China; Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering , Xi'an Jiaotong University , China"},{"name":"Haokun Zhang","slug":"haokun-zhang","given":"Haokun","family":"Zhang","affiliation":"School of Computer Science and Technology , Xi'an Jiaotong University , China; Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering , Xi'an Jiaotong University , China"},{"name":"Huang Xu","slug":"huang-xu","given":"Huang","family":"Xu","affiliation":"Servyou Software Group Co. , Ltd; Hangzhou City University , China"},{"name":"Yaodong Zhang","slug":"yaodong-zhang","given":"Yaodong","family":"Zhang","affiliation":"Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering , Xi'an Jiaotong University , China"},{"name":"Yuefei Wu","slug":"yuefei-wu","given":"Yuefei","family":"Wu","affiliation":"School of Computer Science and Technology , Xi'an Jiaotong University , China; Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering , Xi'an Jiaotong University , China"},{"name":"Bo Dong","slug":"bo-dong","given":"Bo","family":"Dong","affiliation":"Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering , Xi'an Jiaotong University , China; School of Distance Education , Xi'an Jiaotong University , China"},{"name":"Qinghua Zheng","slug":"qinghua-zheng","given":"Qinghua","family":"Zheng","affiliation":"School of Computer Science and Technology , Xi'an Jiaotong University , China; Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering , Xi'an Jiaotong University , China"}],"abstract":"Sequence labeling serves as the most commonly used scheme for Chinese named entity recognition(NER). However, traditional sequence labeling methods classify tokens within an entity into different classes according to their positions. As a result, different tokens in the same entity may be learned with representations that are isolated and unrelated in target representation space, which could finally negatively affect the subsequent performance of token classification. In this paper, we point out and define this problem as Entity Representation Segmentation in Label-semantics. And then we present NerCo: Named entity recognition with Contrastive learning, a novel NER framework which can better exploit labeled data and avoid the above problem. Following the pretrain-finetune paradigm, NerCo firstly guides the encoder to learn powerful label-semantics based representations by gathering the encoded token representations of the same Semantic Class while pushing apart that of different. Subsequently, NerCo finetunes the learned encoder for final entity prediction. Extensive experiments on several datasets demonstrate that our framework can consistently improve the baseline and achieve state-of-the-art performance.","doi":"10.24963/ijcai.2023/587","url":"https://ijcai.org/proceedings/2023/587","pdf":"https://ijcai.org/proceedings/2023/0587.pdf","markdown":"https://ijcai.org/proceedings/2023/587.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/587","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Natural Language Processing","track":"Main Track","number":587,"pages":{"first":5287,"last":5295},"keywords":["Natural Language Processing: NLP: Named entities","Natural Language Processing: NLP: Tagging, chunking, and parsing","Natural Language Processing: NLP: Information extraction"],"videos":[],"references":[{"position":1,"raw":"[Che et al., 2013] Wanxiang Che, Mengqiu Wang, Christo- pher D. 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