基于描述性文本的关系指示词抽取方法研究——以我国传统刺绣为例
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[1]何琳，马晓雯，喻雪寒，等.典籍事件触发动词识别研究：基于《左传》的文本实验[J].图书情报工作，2022，66（05）：133-141.
[2]仲伟峰，杨航，陈玉博，等.基于联合标注和全局推理的篇章级事件抽取[J].中文信息学报，2019，33（09）：88-95+106.
[3]李井竹，陆玉婷，顾进广.基于句法分析的临床指南事件及事件关系提取[J].武汉大学学报（理学版），2015，61（02）：156-162.
[4]冷根，周允升，余敦辉，等.基于关系触发词与多特征的中文人物关系抽取[J].计算机工程与设计，2024，45（01）：282-290.
[5]陈世婕，王卫星，彭莉.基于多尺度网络的苗绣绣片纹样分割算法研究[J].计算机技术与发展，2023，33（11）：149-155.
[6]周泽聿，王昊，张小琴，等.基于Xception-TD的中华传统刺绣分类模型构建[J].数据分析与知识发现，2022，6（Z1）：338-347.
[7]刘羿漩，葛广英，齐振岭，等.基于改进深度卷积生成对抗网络的刺绣图像修复[J].激光与光电子学进展，2023，60（20）：68-78.
[8]熊瑛.地方志中民间手工艺史料的发掘与利用——以明代织绣为例[J].民族艺术研究，2016，29（2）：234-241.
[9]丁敬达，杜德慧.文化空间视域的刺绣非遗演化探析[J].图书馆杂志，2025，44（03）：105-112.
[10]Werlich E. A text grammar of English[M]. Heidelberg: Quelle & Meyer, 1976.
[11]Biber D. Variation across speech and writing[M]. Cambridge: Cambridge University Press, 1988.
[12]Longacre R E. The grammar of discourse[M]. New York: Plenum Press, 1996.
[13]郭喜跃，何婷婷.信息抽取研究综述[J].计算机科学，2015，42（02）：14-17+38.
[14]Sarawagi S. Information extraction[M]. Now Publishers Inc, 2008.
[15]高跃.基于子句的开放域信息抽取[D].四川大学，2021.
[16]杨博，蔡东风，杨华.开放式信息抽取研究进展[J].中文信息学报，2014，28（4）：12.
[17]杨志伟.面向非结构化文本的命名实体识别方法研究[D].吉林大学，2023.
[18]Zhang Y, Yang J. Chinese NER using lattice LSTM [C]//Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, Melbourne, Jul 15 - 20, 2018. Stroudsburg: ACL, 2018:1554 - 1564.
[19]Mar T, Peng M L, Zhang Q, et al. Simplify the usage of lexicon in Chinese NER [C]//Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Jul 5 - 10, 2020. Stroudsburg: ACL, 2019:2379 - 2389.
[20]Liu W, Xu T G, Xu Q H, et al. An encoding strategy based word - character LSTM for Chinese NER [C]//Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Minneapolis, Jun 2 - 2019. Stroudsburg: ACL, 2020:5951 - 5960.
[21]Wang S, Sun X, Li X, et al. GPT-NER: Named Entity Recognition via Large Language Models [EB/OL]. (2023-10-07) [2025-03-25]. https://arxiv.org/abs/2304.10428.
[22]Hu E J, Shen Y, Wallis P, et al. Lora: Low-Rank Adaptation of Large Language Models[EB/OL]. (2021-10-16) [2025-03-25]. https://arxiv.org/abs/2106.09685.
[23]张逸勤，邓三鸿，王东波.基于生成式大语言模型的非遗文本嵌套命名实体识别研究[J/OL].现代情报，1-19[2025-03-26].http：//kns.cnki.net/kcms/detail/22.1182.G3.20241231.0934.002.html.
[24]Liu X, Huang H, Shi G, Wang B, Lin C Y. Document-level event extraction via heterogeneous graph-based interaction model with a tracker[C]//Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). 2021.
[25]Che W, Feng Y, Qin L, Liu T. N-LTP: An Open-source Neural Language Technology Platform for Chinese[C]//Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Online and Punta Cana, Dominican Republic: Association for Computational Linguistics, 2021: 42-49.
[26]Liu Y. Roberta: A robustly optimized bert pretraining approach[J]. arXiv Preprint arXiv:190711692, 2019, 364.
[27]Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2014: 580-587.
[28]Cui Y M,Che W X,Liu T,et al.Revisiting Pre-trained Models for Chinese Natural Language Processing[C]//Findings of the Association for Computational Linguistics:EMNLP 2020.2020:657-668.
[29]Li J, Sun A, Han J, Li C. FLAT: Chinese NER using flat-lattice transformer[C]//Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020: 6836-6842
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