Research on Event Extraction Model Based on Semantic Features of Chinese Words

Shaowu Zhu

College of Information and Network Security People's Public Security University of China Beijing, China
Haichun Sun

College of Information and Network Security People's Public Security University of China Beijing, China
Hanying Jian

College of Public Security Management People's Public Security University of China Beijing, China

Research on Event Extraction Model Based on Semantic Features of Chinese Words

keywords: BERT, five strokes, Chinese glyph, event extraction, trigger extraction, named entity recognition

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.

mathematics subject classification 2000: 68-T10

reference: Vol. 41, 2022, No. 6, pp. 1625–1647

doi: 10.31577/cai_2022_6_1625

Computing and Informatics

formerly Computers and Artificial Intelligence

Research on Event Extraction Model Based on Semantic Features of Chinese Words