Abstract
We describe the system used in our participation in the AMR Parsing task for SemEval-2016. Our parser does not rely on a syntactic pre-parse, or heavily engineered features, and uses five recurrent neural networks as the key architectural components for estimating AMR graph structure.
Cite
CITATION STYLE
APA
Foland, W. R., & Martin, J. H. (2016). CU-NLP at SemEval-2016 task 8: AMR parsing using lstm-based recurrent neural networks. In SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings (pp. 1197–1201). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s16-1185
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