基于BERT与柱搜索的中文释义生成

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摘要释义生成任务是指为一个目标词生成相应的释义。该文在中文释义生成任务中使用了目标词的上下文信息,并提出了一个基于BERT与柱搜索的释义生成模型。该文构建了包含上下文的CWN中文数据集,同时也在Oxford英文数据集上开展了实验。实验结果显示,该文模型在中英文数据集上性能均有显著提升,其中CWN数据集实验结果相比基线模型BLEU指标提升了10.47,语义相似度指标提升了0.105。语义相似度指标与人工评价结果相关性更高。最后,该文分析了中文释义生成任务仍存在的四个问题。

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	范齐楠
	孔存良
	杨麟儿
	杨尔弘

关键词 ：中文释义生成, BERT, 柱搜索

Abstract：Definition modeling task refers to generate a corresponding definition for a target word. This paper introduces the context information of the target word and proposes a definition generation model based on BERT and beam search. A CWN Chinese definition modeling dataset is constructed with context of the target word. Experiments on this Chinese dataset and the English Oxford dataset show that the model achieves significant improvements in both dataset. Especially in CWN dataset, compared with the baseline model, the BLEU score is improved by 10.47, and the semantic similarity is improved by 0.105.

Key words： Chinese definition modeling BERT beam search

收稿日期: 2021-02-22

中图分类号:

TP391

基金资助:北京语言大学研究生创新基金(中央高校基本科研业务费专项资金)(20YCX139);北京语言大学语言资源高精尖创新中心项目(TYZ19005);国家语委信息化项目(ZDI135-105)

作者简介: 范齐楠(1995—),硕士研究生,主要研究领域为自然语言处理和智能语言学习。E-mail: blcufqn@hotmail.com
孔存良(1995—),博士研究生,主要研究领域为自然语言处理和智能语言学习。E-mail: cunliang.kong@outlook.com
杨麟儿(1983—),通信作者,博士,副教授,主要研究领域为自然语言处理和智能语言学习。E-mail: yangtianlin@blcu.edu.cn

链接本文:

http://jcip.cipsc.org.cn/CN/Y2021/V35/I11/80

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