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吴信东 等: 华谱通: 基于知识推理的家谱问答大语言模型 5597
Linguistics, 2022. 320–335. [doi: 10.18653/v1/2022.acl-long.26]
[35] Wang L, Ma YY, Bi WS, Lv HL, Li YX. An entity extraction pipeline for medical text records using large language models: Analytical
study. Journal of Medical Internet Research, 2024, 26: e54580. [doi: 10.2196/54580]
[36] Bi KF, Xie LX, Zhang HH, Chen X, Gu XT, Tian Q. Accurate medium-range global weather forecasting with 3D neural networks.
Nature, 2023, 619(7970): 533–538. [doi: 10.1038/s41586-023-06185-3]
[37] Li XL, Liang P. Prefix-tuning: Optimizing continuous prompts for generation. In: Proc. of the 59th Annual Meeting of the Association for
Computational Linguistics and the 11th Int’l Joint Conf. on Natural Language Processing (Vol. 1: Long Papers). Pennsylvania:
Association for Computational Linguistics, 2021. 4582–4597. [doi: 10.18653/v1/2021.acl-long.353]
[38] Zhang ZY, Han X, Liu ZY, Jiang X, Sun MS, Liu Q. ERNIE: Enhanced language representation with informative entities. In: Proc. of the
57th Conf. of the Association for Computational Linguistics. Florence: Association for Computational Linguistics, 2019. 1441–1451.
[doi: 10.18653/v1/P19-1139]
®
[39] Robertson S, Zaragoza H. The probabilistic relevance framework: BM25 and beyond. Foundations and Trends in Information Retrieval,
2009, 3(4): 333–389. [doi: 10.1561/1500000019]
[40] Agrawal S, Zhou CT, Lewis M, Zettlemoyer L, Ghazvininejad M. In-context examples selection for machine translation. In: Proc. of the
2023 Findings of the Association for Computational Linguistics. Toronto: Association for Computational Linguistics, 2023. 8857–8873.
[doi: 10.18653/v1/2023.findings-acl.564]
[41] Qiao SJ, Yang GP, Yu Y, Han N, Tan X, Qu LL, Ran LQ, Li H. QA-KGNet: Language model-driven knowledge graph question-
answering model. Ruan Jian Xue Bao/Journal of Software, 2023, 34(10): 4584–4600 (in Chinese with English abstract). http://www.jos.
org.cn/1000-9825/6882.htm [doi: 10.13328/j.cnki.jos.006882]
[42] Luo LH, Li YF, Haffari G, Pan SR. Reasoning on graphs: Faithful and interpretable large language model reasoning. In: Proc. of the 12th
Int’l Conf. on Learning Representations. Vienna: OpenReview.net, 2024. 1–24.
[43] Avila CVS, Vidal VMP, Franco W, Casanova MA. Experiments with text-to-SPARQL based on ChatGPT. In: Proc. of the 18th IEEE Int’l
Conf. on Semantic Computing. Laguna Hills: IEEE, 2024. 277–284. [doi: 10.1109/ICSC59802.2024.00050]
[44] Shao JX, Liu GL, Ji SW. An abnormal data analysis and processing method for genealogy graph databases. In: Proc. of the 2020 IEEE Int’l
Conf. on Knowledge Graph. Nanjing: IEEE, 2020. 131–136. [doi: 10.1109/ICBK50248.2020.00028]
[45] Peng YW, Jiang H, Li RR, Peng ZY. PZXG: A genealogy data service platform for kinship management and application. In: Proc. of the
2020 IEEE Int’l Conf. on Knowledge Graph. Nanjing: IEEE, 2020. 505–512. [doi: 10.1109/ICBK50248.2020.00077]
[46] Dong BB, Zhang Z, Li J, Zhu Y, Bu CY, Wu XD. Hypernode: Entity fusion for data traceability and link prediction. In: Proc. of the 2022
IEEE Int’l Conf. on Data Mining. Orlando: IEEE, 2022. 111–120. [doi: 10.1109/ICDM54844.2022.00021]
附中文参考文献:
[1] 吴信东, 李娇, 周鹏, 卜晨阳. 碎片化家谱数据的融合技术. 软件学报, 2021, 32(9): 2816–2836. http://www.jos.org.cn/1000-9825/6010.
htm [doi: 10.13328/j.cnki.jos.006010]
[3] 吴信东, 盛绍静, 蒋婷婷, 卜晨阳, 吴明辉. 从知识图谱到数据中台: 华谱系统. 自动化学报, 2020, 46(10): 2045–2059. [doi: 10.16383/
j.aas.c200502]
[18] 王乃钰, 叶育鑫, 刘露, 凤丽洲, 包铁, 彭涛. 基于深度学习的语言模型研究进展. 软件学报, 2021, 32(4): 1082–1115. http://www.jos.
org.cn/1000-9825/6169.htm [doi: 10.13328/j.cnki.jos.006169]
[20] 李戈, 彭鑫, 王千祥, 谢涛, 金芝, 王戟, 马晓星, 李宣东. 大模型: 基于自然交互的人机协同软件开发与演化工具带来的挑战. 软件学
报, 2023, 34(10): 4601–4606. http://www.jos.org.cn/1000-9825/7008.htm [doi: 10.13328/j.cnki.jos.007008]
[23] 李诗晨, 王中卿, 周国栋. 大语言模型驱动的跨领域属性级情感分析. 软件学报, 2025, 36(2): 644–659. http://www.jos.org.cn/1000-
9825/7156.htm [doi: 10.13328/j.cnki.jos.007156]
[24] 梁峥, 王宏志, 戴加佳, 邵心玥, 丁小欧, 穆添愉. 预训练语言模型实体匹配的可解释性. 软件学报, 2023, 34(3): 1087–1108. http://
www.jos.org.cn/1000-9825/6794.htm [doi: 10.13328/j.cnki.jos.006794]
[25] 琚生根, 黄方怡, 孙界平. 融合预训练语言模型的成语完形填空算法. 软件学报, 2022, 33(10): 3793–3805. http://www.jos.org.cn/1000-
9825/6307.htm [doi: 10.13328/j.cnki.jos.006307]
[41] 乔少杰, 杨国平, 于泳, 韩楠, 覃晓, 屈露露, 冉黎琼, 李贺. QA-KGNet: 一种语言模型驱动的知识图谱问答模型. 软件学报, 2023,
34(10): 4584–4600. http://www.jos.org.cn/1000-9825/6882.htm [doi: 10.13328/j.cnki.jos.006882]

