@InProceedings{lee-lee-tseng:2017:SemEval,
  author    = {Lee, Lung-Hao  and  Lee, Kuei-Ching  and  Tseng, Yuen-Hsien},
  title     = {The NTNU System at SemEval-2017 Task 10: Extracting Keyphrases and Relations from Scientific Publications Using Multiple Conditional Random Fields},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {951--955},
  abstract  = {This study describes the design of the NTNU system for the ScienceIE task at
	the SemEval 2017 workshop. We use self-defined feature templates and multiple
	conditional random fields with extracted features to identify keyphrases along
	with categorized labels and their relations from scientific publications. A
	total of 16 teams participated in evaluation scenario 1 (subtasks A, B, and C),
	with only 7 teams competing in all sub-tasks. Our best micro-averaging F1
	across the three subtasks is 0.23, ranking in the middle among all 16
	submissions.},
  url       = {http://www.aclweb.org/anthology/S17-2165}
}