@InProceedings{buys-blunsom:2017:SemEval,
  author    = {Buys, Jan  and  Blunsom, Phil},
  title     = {Oxford at SemEval-2017 Task 9: Neural AMR Parsing with Pointer-Augmented Attention},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {914--919},
  abstract  = {We present a neural encoder-decoder AMR parser that extends an attention-based
	model by predicting the alignment between graph nodes and sentence tokens
	explicitly with a pointer mechanism. Candidate lemmas are predicted as a
	pre-processing step so that the lemmas of lexical concepts, as well as constant
	strings, are factored out of the graph linearization and recovered through the
	predicted alignments. The approach does not rely on syntactic parses or
	extensive external resources. Our parser obtained 59% Smatch on the SemEval
	test set.},
  url       = {http://www.aclweb.org/anthology/S17-2157}
}