Construction and Inference Technique of Large-Scale Chinese Concreteness Lexicon

被引：0
|
作者：
Xie Z. [1 ]
Bi R. [1 ]
机构：
[1] School of Computer Science, Fudan University, Shanghai
来源：
Beijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis | 2022年 / 58卷 / 01期
关键词：
Concreteness inference; Multi-layer perceptron; Natural language processing; Word concreteness;
D O I：
10.13209/j.0479-8023.2021.100
中图分类号：
学科分类号：
摘要：
To solve the resource-lack problem of Chinese word concreteness, this paper designs and implements an automatic method to construct Chinese concreteness lexicon. By making full use of the existing resource of English word concreteness, it builds up a large-scale Chinese concreteness lexicon based on pretrained word embeddings and an MLP concreteness regression model. In addition, it proposes the concreteness inference tasks on the word level and on the sentence level, and manually constructs the corresponding datasets for evaluation the performance of the Chinese concreteness lexicon on these tasks. Experimental results show that the constructed concreteness lexicon can perform the two inference tasks effectively. © 2022 Peking University.
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页码：1 / 6
页数：5
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