IRCMS at SemEval-2018 Task 7 : Evaluating a basic CNN Method and Traditional Pipeline Method for Relation Classification
Zhongbo Yin, Zhunchen Luo, Luo Wei, Bin Mao, Tian Changhai, Yuming Ye, Shuai Wu · 2018
This paper presents our participation for sub-task1 (1.1 and 1.2) in SemEval 2018 task 7: Semantic Relation Extraction and Classification in Scientific Papers (Gábor et al., 2018).We experimented on this task with two methods: CNN method and traditional pipeline method.We use the context between two entities (included) as input information for both methods, which extremely reduce the noise effect.For the CNN method, we construct a simple convolution neural network to automatically learn features from raw texts without any manual processing.Moreover, we use the softmax function to classify the entity pair into a specific relation category.For the traditional pipeline method, we use the Hackabout method as a representation which is described in section3.5.The CNN method's result is much better than traditional pipeline method (49.1% vs. 42.3% and 71.1% vs. 54.6% ).