@InProceedings{wang-bao-gao:2016:COLING,
  author    = {Wang, Weihua  and  Bao, Feilong  and  Gao, Guanglai},
  title     = {Mongolian Named Entity Recognition System with Rich Features},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {505--512},
  abstract  = {In this paper, we first build a manually annotated named entity corpus of
	Mongolian. Then, we propose three morphological processing methods and study
	comprehensive features, including syllable features, lexical features, context
	features, morphological features and semantic features in Mongolian named
	entity recognition. Moreover, we also evaluate the influence of word cluster
	features on the system and combine all features together eventually. The
	experimental result shows that segmenting each suffix into an individual token
	achieves better results than deleting suffixes or using the suffixes as
	feature. The system based on segmenting suffixes with all proposed features
	yields benchmark result of F-measure=84.65 on this corpus.
	Author{3}{Affiliation}},
  url       = {http://aclweb.org/anthology/C16-1049}
}