%0 Journal Article %A ZHENG Hao %A LI Yuan %A SHEN Wei %A CHEN Jiajie %T Chinese Complex Sentence Relation Identification Based on Attention Mechanism and Graph Convolutional Network %D 2023 %R %J Journal of Chinese Information Processing %P 60-67 %V 36 %N 11 %X Relation identification of complex sentences is to distinguish the categories of semantic relations of sub-sentences. Focused on the sentences without explicit connectives, this paper applies the Attention mechanism combined with the GCN to classify the semantic relationship of Chinese complex sentences. The Bert based sentence representation formed by word vector is input into the Bi-LSTM. The sentence position representation is obtained and weighted via attention mechanism. A graph network is then constructed to capture the semantic information between sentences. The experiments on the CCCS and CDTB datasets reveal that the proposed method achieves 76.2% and 74.4% F1 value, respectively, increasing about 2.1% compared with the previous best models. %U http://jcip.cipsc.org.cn/EN/abstract/article_3424.shtml