Improving Implicit Semantic Role Labeling by Predicting Semantic Frame Arguments

@inproceedings{Do2017ImprovingIS,
  title={Improving Implicit Semantic Role Labeling by Predicting Semantic Frame Arguments},
  author={Quynh Ngoc Thi Do and Steven Bethard and Marie-Francine Moens},
  booktitle={IJCNLP},
  year={2017}
}
Implicit semantic role labeling (iSRL) is the task of predicting the semantic roles of a predicate that do not appear as explicit arguments, but rather regard common sense knowledge or are mentioned earlier in the discourse. We introduce an approach to iSRL based on a predictive recurrent neural semantic frame model (PRNSFM) that uses a large unannotated corpus to learn the probability of a sequence of semantic arguments given a predicate. We leverage the sequence probabilities predicted by the… CONTINUE READING
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