@InProceedings{tokunaga-nishikawa-iwakura:2017:RANLP,
  author    = {Tokunaga, Takenobu  and  Nishikawa, Hitoshi  and  Iwakura, Tomoya},
  title     = {An Eye-tracking Study of Named Entity Annotation},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {758--764},
  abstract  = {Utilising effective features in machine learning-based natural language
	processing (NLP) is crucial in achieving good performance for a given NLP task.
	 The paper describes a pilot study on the analysis of eye-tracking data during
	named entity (NE) annotation, aiming at obtaining insights into effective
	features for the NE recognition task. The eye gaze data were collected from 10
	annotators and analysed regarding working time and fixation distribution.  The
	results of the preliminary qualitative analysis showed that human annotators
	tend to look at broader contexts around the target NE than recent
	state-of-the-art automatic NE recognition systems and to use predicate argument
	relations to identify the NE categories.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_097}
}