@InProceedings{marsi-EtAl:2017:SemEval,
  author    = {Marsi, Erwin  and  Sikdar, Utpal Kumar  and  Marco, Cristina  and  Barik, Biswanath  and  S{\ae}tre, Rune},
  title     = {NTNU-1$@$ScienceIE at SemEval-2017 Task 10: Identifying and Labelling Keyphrases with 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     = {938--941},
  abstract  = {We present NTNU's systems for Task A (prediction of keyphrases) and Task B
	(labelling as Material, Process or Task) at SemEval 2017 Task 10: Extracting
	Keyphrases and Relations from Scientific Publications
	\cite{augenstein2017scienceie}. Our approach relies on supervised machine
	learning using Conditional Random Fields. Our system yields a micro F-score of
	0.34 for Tasks A and B combined on the test data. For Task C (relation
	extraction), we relied on an independently developed system described in
	\cite{Barik:2017}. For the full Scenario 1 (including relations), our approach
	reaches a micro F-score of 0.33 (5th place). Here we describe our systems,
	report results and discuss errors.},
  url       = {http://www.aclweb.org/anthology/S17-2162}
}