孙媛,王丽客,郭莉莉. 基于改进词向量GRU神经网络模型的藏语实体关系抽取[J]. 中文信息学报, 2019, 33(6): 35-41.
SUN Yuan, WANG Like, GUO Lili. Tibetan Entity Relation Extraction Based on Optimized Word Embedding with GRU Neural Network. , 2019, 33(6): 35-41.
Tibetan Entity Relation Extraction Based on Optimized Word Embedding with GRU Neural Network
SUN Yuan1,2, WANG Like1,2, GUO Lili1,2
1.School of Information Engineering, Minzu University of China, Beijing 100081, China; 2.Minority Languages Branch, National Language Resource and Monitoring Research Center, Minzu University of China, Beijing 100081, China
Abstract：To facilitate the structural analysis Tibetan and development of deeper of Tibetan knowledge, this paper proposes a method for Tibetan entity relation extraction based on optimized word vectors with GRU neural network model. In the training of the model, we apply the optimized word vector. In order to get a relatively good word vector model, we introduce the Tibetan syllable vector, the syllable position vector, part of speech vector and so on to further optimize the word vector. And we also select Tibetan lexical features and Tibetan sentence features. Experiments show that the proposed method achieves F1 value of 78.43%.
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2019, Vol. 33 
