@InProceedings{perezbeltrachini-gardent:2017:INLG2017,
  author    = {Perez-Beltrachini, Laura  and  Gardent, Claire},
  title     = {Analysing Data-To-Text Generation Benchmarks},
  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     = {238--242},
  abstract  = {A generation system can only be as good as the data it is trained on. In this
	short paper, we propose a methodology for analysing data-to-text corpora used
	for training Natural Language Generation (NLG) systems. We apply this
	methodology to three existing benchmarks. We conclude by eliciting a set of
	criteria for the creation of a data-to-text benchmark which could help better
	support the development, evaluation and comparison of linguistically
	sophisticated data-to-text generators.},
  url       = {http://www.aclweb.org/anthology/W17-3537}
}