会议论文

Liu, Y.

英文

Communications in Computer and Information Science

1865-0929

2021

1356 CCIS

147-159

5th China Conference on Knowledge Graph, and Semantic Computing, CCKS 2020

12 November 2020 through 15 November 2020

Chen H.Liu K.Sun Y.Wang S.Hou L.

Springer Science and Business Media Deutschland GmbH

9789811619632

10.1007/978-981-16-1964-9_12

Acknowledgements. This research was funded by the National Natural Science Foundation of China, grant number 61402220, the Philosophy and Social Science Foundation of Hunan Province, grant number 16YBA323, the Scientic Research Fund of Hunan Provincial Education Department for excellent talents, grant number 18B279, the key program of Scientic Research Fund of Hunan Provincial Education Department, grant number 19A439, the Project supported by the Natural Science Foundation of Hunan Province, China, grant number 2020JJ4525.

本校为第一机构

Event Detection (ED) is a task that aims to recognize triggers and identify the event type in sentences. Syntactic information plays a crucial role in event detection model accurately to recognize the triggers and event type. The previous works commonly use word embedding to obtain context representation that cannot fully exploit syntactic information. In this paper, we propose a novel model HSGCN (Hybrid Syntactic Graph Convolutional Networks) for Chinese event detection, which utilizes graph convolutional networks to generate sentence-level f...