Unsupervised Argument Identification for Semantic Role Labeling

@inproceedings{Abend2009UnsupervisedAI,
  title={Unsupervised Argument Identification for Semantic Role Labeling},
  author={Omri Abend and Roi Reichart and Ari Rappoport},
  booktitle={ACL/IJCNLP},
  year={2009}
}
The task of Semantic Role Labeling (SRL) is often divided into two sub-tasks: verb argument identification, and argument classification. Current SRL algorithms show lower results on the identification sub-task. Moreover, most SRL algorithms are supervised, relying on large amounts of manually created data. In this paper we present an unsupervised algorithm for identifying verb arguments, where the only type of annotation required is POS tagging. The algorithm makes use of a fully unsupervised… CONTINUE READING
Highly Cited
This paper has 39 citations. REVIEW CITATIONS