A Joint Sequential and Relational Model for Frame-Semantic Parsing

@inproceedings{Yang2017AJS,
  title={A Joint Sequential and Relational Model for Frame-Semantic Parsing},
  author={Bishan Yang and Tom Michael Mitchell},
  booktitle={Conference on Empirical Methods in Natural Language Processing},
  year={2017}
}
We introduce a new method for framesemantic parsing that significantly improves the prior state of the art. [] Key Method The two networks are integrated into a single model via knowledge distillation, and a unified graphical model is employed to jointly decode frames and semantic roles during inference. Experiments on the standard FrameNet data show that our model significantly outperforms existing neural and non-neural approaches, achieving a 5.7 F1 gain over the current state of the art, for full frame…
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62 Citations
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