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Conference Paper: Transforming dependencies into phrase structures

TitleTransforming dependencies into phrase structures
Authors
Kong, LingpengRush, Alexander M.Smith, Noah A.
Issue Date2015
Citation
2015 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 31 May-5 June 2015. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics, 2015, p. 788-798 How to Cite?
DOI: http://dx.doi.org/10.3115/v1/n15-1080
Abstract© 2015 Association for Computational Linguistics. We present a new algorithm for transforming dependency parse trees into phrase-structure parse trees. We cast the problem as structured prediction and learn a statistical model. Our algorithm is faster than traditional phrasestructure parsing and achieves 90.4% English parsing accuracy and 82.4% Chinese parsing accuracy, near to the state of the art on both benchmarks.
Persistent Identifierhttp://hdl.handle.net/10722/296121

 

DC FieldValueLanguage
dc.contributor.authorKong, Lingpeng-
dc.contributor.authorRush, Alexander M.-
dc.contributor.authorSmith, Noah A.-
dc.date.accessioned2021-02-11T04:52:52Z-
dc.date.available2021-02-11T04:52:52Z-
dc.date.issued2015-
dc.identifier.citation2015 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 31 May-5 June 2015. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics, 2015, p. 788-798-
dc.identifier.urihttp://hdl.handle.net/10722/296121-
dc.description.abstract© 2015 Association for Computational Linguistics. We present a new algorithm for transforming dependency parse trees into phrase-structure parse trees. We cast the problem as structured prediction and learn a statistical model. Our algorithm is faster than traditional phrasestructure parsing and achieves 90.4% English parsing accuracy and 82.4% Chinese parsing accuracy, near to the state of the art on both benchmarks.-
dc.languageeng-
dc.relation.ispartofProceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleTransforming dependencies into phrase structures-
dc.typeConference_Paper-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3115/v1/n15-1080-
dc.identifier.scopuseid_2-s2.0-84960154992-
dc.identifier.spage788-
dc.identifier.epage798-

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