@InProceedings{komninos-manandhar:2017:Short,
  author    = {Komninos, Alexandros  and  Manandhar, Suresh},
  title     = {Feature-Rich Networks for Knowledge Base Completion},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {324--329},
  abstract  = {We propose jointly modelling Knowledge Bases and aligned text with Feature-Rich
	Networks. Our models perform Knowledge Base Completion by learning to represent
	and compose diverse feature types from partially aligned and noisy resources.
	We perform experiments on Freebase utilizing additional entity type information
	and syntactic textual relations. Our evaluation suggests that the proposed
	models can better incorporate side information than previously proposed
	combinations of bilinear models with convolutional neural networks, showing
	large improvements when scoring the plausibility of unobserved facts with
	associated textual mentions.},
  url       = {http://aclweb.org/anthology/P17-2051}
}