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| 基于跨语言数据增强的事件同指消解方法 | |
| 引用本文： | 程昊熠,李培峰,朱巧明.基于跨语言数据增强的事件同指消解方法[J].中文信息学报,2022,36(3):19-26. |
| 作者姓名： | 程昊熠 李培峰 朱巧明 |
| 作者单位： | 1.苏州大学 计算机科学与技术学院,江苏 苏州 215006; 2.江苏省计算机信息技术处理重点实验室,江苏 苏州 215006 |
| 基金项目： | 国家自然科学基金(61773276,61472265,61772354);江苏高校优势学科建设工程资助项目 |
| 摘 要： | 事件同指消解是一个具有挑战性的自然语言处理任务,它在事件抽取、问答系统和阅读理解等任务中发挥着重要作用.现存的事件同指消解语料库的一个问题是标注规模较小,无法训练出高效能的模型.为了解决上述问题,该文提出了一个基于跨语言数据增强的事件同指消解神经网络模型ECR_CDA(Event Coreference Resolut... |
| 关 键 词： | 事件同指 事件实例短句 中英跨语言学习 全局优化方法 |
Cross-lingual Data Augmentation Based Event Coreference Resolution |
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| CHENG Haoyi,LI Peifeng,ZHU Qiaoming.Cross-lingual Data Augmentation Based Event Coreference Resolution[J].Journal of Chinese Information Processing,2022,36(3):19-26. | |
| Authors: | CHENG Haoyi LI Peifeng ZHU Qiaoming |
| Affiliation: | 1.School of Computer Sciences and Technology,Soochow University, Suzhou, Jiangsu 215006, China; 2.Provincial Key Laboratory for Computer Information Processing Technology, Suzhou, Jiangsu 215006, China |
| Abstract: | Event coreference resolution is a challenging task with wide application in event extraction, QA system, and reading comprehension. The best use the existing small-scale public corpus, this paper introduces a neural network model ECR_CDA based on cross-lingual data augmentation. This model enhances the corpus through the translation of Chinese and English corpus, and improves the performance of event coreference resolution via the cross-lingual learning of Chinese and English models by sharing the model parameters. The experimental results on ACE 2005 English test set show that ECR_CDA is superior to the most advanced baseline. |
| Keywords: | event coreference single event Chinese and English cross-lingual learning global optimization method |
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