Pairwise Relation Classification with Mirror Instances and a Combined Convolutional Neural Network

COLING 2016 Jianfei YuJing Jiang

Relation classification is the task of classifying the semantic relations between entity pairs in text. Observing that existing work has not fully explored using different representations for relation instances, especially in order to better handle the asymmetry of relation types, in this paper, we propose a neural network based method for relation classification that combines the raw sequence and the shortest dependency path representations of relation instances and uses mirror instances to perform pairwise relation classification... (read more)

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