Abstract
We propose an efficient dynamic oracle for training the 2-Planar transition-based parser, a linear-time parser with over 99% coverage on non-projective syntactic corpora. This novel approach outperforms the static training strategy in the vast majority of languages tested and scored better on most datasets than the arc-hybrid parser enhanced with the Swap transition, which can handle unrestricted nonprojectivity.
Cite
CITATION STYLE
Fernández-González, D., & Gómez-Rodríguez, C. (2018). A dynamic oracle for linear-time 2-planar dependency parsing. In NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference (Vol. 2, pp. 386–392). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/n18-2062
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