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dc.contributor.authorGómez-Rodríguez, Carlos
dc.date.accessioned2017-07-17T14:22:34Z
dc.date.available2017-07-17T14:22:34Z
dc.date.issued2016-12
dc.identifier.citationCarlos Gómez-Rodríguez, Restricted Non-Projectivity: Coverage vs. Efficiency, Computational Linguistics, 42(4):809-817, 2016es_ES
dc.identifier.issn0891-2017
dc.identifier.urihttp://hdl.handle.net/2183/19288
dc.description.abstract[Abstract] In the last decade, various restricted classes of non-projective dependency trees have been proposed with the goal of achieving a good tradeoff between parsing efficiency and coverage of the syntactic structures found in natural languages. We perform an extensive study measuring the coverage of a wide range of such classes on corpora of 30 languages under two different syntactic annotation criteria. The results show that, among the currently known relaxations of projectivity, the best tradeoff between coverage and computational complexity of exact parsing is achieved by either 1-endpoint-crossing trees or MH k trees, depending on the level of coverage desired. We also present some properties of the relation of MH k trees to other relevant classes of trees.es_ES
dc.description.sponsorshipMinisterio de Economía y Competitividad; FFI2014-51978-C2-2-Res_ES
dc.language.isoenges_ES
dc.relation.urihttp://www.mitpressjournals.org/doi/10.1162/COLI_a_00267es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rightsComputational Linguistics is Open Access. All content is freely available in electronic format (Full text HTML, PDF, and PDF Plus) to readers across the globe. All articles are published under a CC BY 4.0 license. For more information on allowed uses, please view the CC license.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.titleRestricted Non-Projectivity: Coverage vs. Efficiencyes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleComputational Linguisticses_ES
UDC.volume42es_ES
UDC.issue4es_ES
UDC.startPage809es_ES
UDC.endPage817es_ES


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