关键词: 事件线索检测, 神经网络, 长短时记忆网络（LSTM）

Abstract: Event nugget detection aims to extract words or phrases which trigger events from the free text automatically. Existing methods about English event nugget detection rely on feature extraction tools, which will cause error propagation. Besides, they ignore the dependency between the candidate word and the context and the semantic     information of the sentence, which are helpful to detect event nugget. This paper proposes a neural network method, which uses bidirectional long short-term memory neural network (Bi-LSTM) to crawl the dependency of sentence context while using the gated recurrent neural network (GRNN) to learn sentence semantic representation. Then this paper combines these information to improve the ability of identifying event nugget. The experimental results on the corpus of KBP 2015 evaluation show that the proposed method is effective and significantly higher than baseline methods.

Key words: event nugget detection, neural network, long short-term memory (LSTM)