Viable Dependency Parsing as Sequence Labeling
Use this link to cite
http://hdl.handle.net/2183/35098Collections
- GI-LYS - Congresos, conferencias, etc. [71]
- OpenAIRE [366]
Metadata
Show full item recordTitle
Viable Dependency Parsing as Sequence LabelingDate
2019-06Citation
Michalina Strzyz, David Vilares, and Carlos Gómez-Rodríguez. 2019. Viable Dependency Parsing as Sequence Labeling. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 717–723, Minneapolis, Minnesota. Association for Computational Linguistics. doi: 10.18653/v1/N19-1077
Abstract
[Abstract]: We recast dependency parsing as a sequence labeling problem, exploring several encodings of dependency trees as labels. While dependency parsing by means of sequence labeling had been attempted in existing work, results suggested that the technique was impractical. We show instead that with a conventional BILSTM-based model it is possible to obtain fast and accurate parsers. These parsers are conceptually simple, not needing traditional parsing algorithms or auxiliary structures. However, experiments on the PTB and a sample of UD treebanks show that they provide a good speed-accuracy tradeoff, with results competitive with more complex approaches.
Keywords
Dependency parsing
Dependency trees
Encodings
Parsing algorithm
Sequence Labeling
Speed accuracy
Treebanks
Computational linguistics
Dependency trees
Encodings
Parsing algorithm
Sequence Labeling
Speed accuracy
Treebanks
Computational linguistics
Editor version
Rights
Atribución 3.0 España