@InProceedings{gardent-EtAl:2017:INLG2017,
  author    = {Gardent, Claire  and  Shimorina, Anastasia  and  Narayan, Shashi  and  Perez-Beltrachini, Laura},
  title     = {The WebNLG Challenge: Generating Text from RDF Data},
  booktitle = {Proceedings of the 10th International Conference on Natural Language Generation},
  month     = {September},
  year      = {2017},
  address   = {Santiago de Compostela, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {124--133},
  abstract  = {The WebNLG challenge consists in mapping sets of RDF triples to text. It
	provides a common benchmark on which to train, evaluate and compare
	“microplanners”, i.e. generation systems that verbalise a given content by
	making a range of complex interacting choices including referring expression
	generation, aggregation, lexicalisation, surface realisation and sentence
	segmentation. In this paper, we introduce the microplanning task, describe data
	preparation, introduce our evaluation methodology, analyse participant results
	and provide a brief description of the participating systems.},
  url       = {http://www.aclweb.org/anthology/W17-3518}
}