RESEARCH ON EVENT EXTRACTION MODEL BASED ON SEMANTIC FEATURES OF CHINESE WORDS

被引：0

作者：

Zhu, Shaowu ^{[1
]}

Sun, Haichun ^{[1
]}

Jian, Hanying ^{[2
]}

机构：

[1] Peoples Publ Secur Univ China, Coll Informat & Network Secur, Beijing, Peoples R China

[2] Peoples Publ Secur Univ China, Coll Publ Secur Management, Beijing, Peoples R China

来源：

COMPUTING AND INFORMATICS | 2022年 / 41卷 / 06期

基金：

中国国家自然科学基金; 北京市自然科学基金;

关键词：

BERT; five strokes; Chinese glyph; event extraction; trigger extraction; named entity recognition; TRIGGER;

D O I：

10.31577/cai202261625

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Event Extraction (EE) is an important task in Natural Language Understanding (NLU). As the complexity of Chinese structure, Chinese EE is more difficult than English EE. According to the characteristics of Chinese, this paper designed a Semantic-GRU (Sem-GRU) model, which integrates Chinese word context semantics, Chinese word glyph semantics and Chinese word structure semantics. And this paper uses the model for Chinese Event Trigger Extraction (ETE) task. The experiment is compared in two tasks: ETE and Named Entity Recognition (NER). In ETE, the paper uses ACE 2005 Chinese event dataset to compare the existing research, the effect reaches 75.8 %. In NER, the paper uses MSRA dataset, which reaches 90.3 %, better than other models.

引用

页码：1625 / 1647

页数：23

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