@InProceedings{jin-kawahara-kurohashi:2017:EACLlong,
  author    = {Jin, Gongye  and  Kawahara, Daisuke  and  Kurohashi, Sadao},
  title     = {Improving Chinese Semantic Role Labeling using High-quality Surface and Deep Case Frames},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {568--577},
  abstract  = {This paper presents a method for applying automatically acquired knowledge to
	semantic role labeling (SRL). We use a large amount of automatically extracted
	knowledge to improve the performance of SRL.  We present two varieties of
	knowledge, which we call surface case frames and deep case frames. Although the
	surface case frames are compiled from syntactic parses and can be used as rich
	syntactic knowledge, they have limited capability for resolving semantic
	ambiguity. To compensate the deficiency of the surface case frames, we compile
	deep case frames from automatic semantic roles. We also consider quality
	management for both types of knowledge in order to get rid of the noise brought
	from the automatic analyses. The experimental results show that Chinese SRL can
	be improved using automatically acquired knowledge and the quality management
	shows a positive effect on this task.},
  url       = {http://www.aclweb.org/anthology/E17-1054}
}