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中文连动句语义关系识别研究

Semantic Relation Recognition of Chinese Serial-verb Sentences

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连动句是形如"NP+VP1+VP2"的句子,句中含有两个或两个以上的动词(或动词结构)且动词的施事为同一对象.相同结构的连动句可以表示多种不同的语义关系.该文基于前人对连动句中VP1和VP2之间的语义关系分类,标注了连动句语义关系数据集,基于神经网络完成了对连动句语义关系的识别.该方法将连动句语义识别任务进行分解,基于BERT进行编码,利用BiLSTM-CRF先识别出连动句中连动词(VP)及其主语(NP),再基于融合连动词信息的编码,利用BiLSTM-Attention对连动词进行关系判别,实验结果验证了该文所提方法的有效性.
Serial-verb sentence contains two or more verbs(or verb structures)sharing the same agent with the form of"NP+VP1+VP2".Sentences with the same serial-verb structures can express a variety of different semantic re-lation.In this paper,we build a data set of serial verb sentences,and propose a neural network model for recognition of semantic relation in serial verbs.First,the serial-verb sentences are encoded with Bert.Second,BiLSTM-CRF is used to identify the serial verbs and their subjects.Then,based on the embedding fused with serial verbs,the rela-tion recognition of serial verbs is implemented using BiLSTM-Attention.The experimental results prove the effec-tiveness of the proposed method.

serial-verb structureneural networksemantic relation recognition of serial-verb sentences

孙超、曲维光、魏庭新、顾彦慧、李斌、周俊生

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南京师范大学中北学院,江苏丹阳 212334

南京师范大学计算机与电子信息学院/人工智能学院,江苏南京 210023

昆山震川高级中学,江苏苏州 215300

南京师范大学文学院,江苏南京 210097

南京师范大学国际文化教育学院,江苏南京 210097

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连动结构 神经网络 连动句语义关系识别

国家社会科学基金

21&ZD288

2024

中文信息学报
中国中文信息学会,中国科学院软件研究所

中文信息学报

CSTPCDCHSSCD北大核心
影响因子:0.8
ISSN:1003-0077
年,卷(期):2024.38(5)
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