Towards Semi-Supervised Learning for Deep Semantic Role Labeling

@inproceedings{Mehta2018TowardsSL,
  title={Towards Semi-Supervised Learning for Deep Semantic Role Labeling},
  author={Sanket Vaibhav Mehta and Jay Yoon Lee and Jaime G. Carbonell},
  booktitle={EMNLP},
  year={2018}
}
Neural models have shown several state-of-the-art performances on Semantic Role Labeling (SRL). However, the neural models require an immense amount of semantic-role corpora and are thus not well suited for low-resource languages or domains. The paper proposes a semi-supervised semantic role labeling method that outperforms the state-of-the-art in limited SRL training corpora. The method is based on explicitly enforcing syntactic constraints by augmenting the training objective with a syntactic… CONTINUE READING
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