@InProceedings{steinberger-krejzl-brychcin:2017:RANLP,
  author    = {Steinberger, Josef  and  Krejzl, Peter  and  Brychc\'{i}n, Tom\'{a}\v{s}},
  title     = {Pyramid-based Summary Evaluation Using Abstract Meaning Representation},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {701--706},
  abstract  = {We propose a novel metric for evaluating
	summary content coverage. The evaluation
	framework follows the Pyramid approach
	to measure how many summarization
	content units, considered important by
	human annotators, are contained in an automatic
	summary. Our approach automatizes
	the evaluation process, which does not
	need any manual intervention on the evaluated
	summary side. Our approach compares
	abstract meaning representations of
	each content unit mention and each summary
	sentence. We found that the proposed
	metric complements well the widely-used
	ROUGE metrics.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_090}
}