Joint Learning Improves Semantic Role Labeling

@inproceedings{Toutanova2005JointLI,
  title={Joint Learning Improves Semantic Role Labeling},
  author={Kristina Toutanova and A. Haghighi and Christopher D. Manning},
  booktitle={ACL},
  year={2005}
}
  • Kristina Toutanova, A. Haghighi, Christopher D. Manning
  • Published in ACL 2005
  • Computer Science
  • Despite much recent progress on accurate semantic role labeling, previous work has largely used independent classifiers, possibly combined with separate label sequence models via Viterbi decoding. This stands in stark contrast to the linguistic observation that a core argument frame is a joint structure, with strong dependencies between arguments. We show how to build a joint model of argument frames, incorporating novel features that model these interactions into discriminative log-linear… CONTINUE READING
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