@InProceedings{biran-mckeown:2017:I17-1,
  author    = {Biran, Or  and  McKeown, Kathleen},
  title     = {Domain-Adaptable Hybrid Generation of RDF Entity Descriptions},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {306--315},
  abstract  = {RDF ontologies provide structured data on entities in many domains and continue
	to grow in size and diversity. While they can be useful as a starting point for
	generating descriptions of entities, they often miss important information
	about an entity that cannot be captured as simple relations. In addition,
	generic approaches to generation from RDF cannot capture the unique style and
	content of specific domains. We describe a framework for hybrid generation of
	entity descriptions, which combines generation from RDF data with text
	extracted from a corpus, and extracts unique aspects of the domain from the
	corpus to create domain-specific generation systems. We show that each
	component of our approach significantly increases the satisfaction of readers
	with the text across multiple applications and domains.},
  url       = {http://www.aclweb.org/anthology/I17-1031}
}