We present an end-to-end method for learning verb-specific semantic frames with feedforward neural network (FNN). Previous work-s in this area mainly adopt a multi-step procedure including part-of-speech tagging, dependency parsing and so on. On the contrary, our method uses a FNN model that maps verb-specific sentences directly to semantic frames. The simple model gets good results on annotated data and has a good generalization ability. Finally we get 0.82 F-score on 63 verbs and 0.73 F-score on 407 verbs.
展开▼
