Before revision:  The only requisite information about unseen types is the name of their labels. We propose a Parasitic Neural Network (PNN), and it can learn a mapping between the general feature representations of text samples and the distributions of unseen types in a shared semantic space. Experiment results show that our model significantly outperforms others on the unseen relation extraction task and achieves effect improvement more than 20\%, when there are not any manual annotations or additional resources .
After revision:  The only requisite information about unseen types is the methods for English are not compatible with that for Chinese. The diversities between Chinese and English linguistics are mainly reflected in morphology and syntax .