Research on Chinese predicate head recognition based on Highway-BiLSTM network - Ruizhang HUANG; Wenfan JIN; Yanping CHEN; Yongbin QIN; Qinghua ZHENG (Tongxin xuebao)
Aiming at the problem of difficult recognition and uniqueness of Chinese predicate head, a Highway-BiLSTM model was proposed.Firstly, multi-layer BiLSTM networks were used to capture multi-granular semantic dependence in a sentence.Then, a Highway network was adopted to alleviate the problem of gradient disappearance.Finally, the output path was optimized by a constraint layer which was designed to guarantee the uniqueness of predicate head.The experimental results show that the proposed method effectively improves the performance of predicate head recognition.