Data-driven deep-syntactic dependency parsing

‘Deep-syntactic’ dependency structures that capture the argumentative, attributive and co-/nordinative relations between full words of a sentence have a great potential for a number/nof NLP-applications. The abstraction degree of these structures is in between the output/nof a syntactic dependency p...

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Detalles Bibliográficos
Autores: Ballesteros, Miguel, Bohnet, Bernd, Mille, Simon, Wanner, Leo
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2016
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/27951
Acceso en línea:http://hdl.handle.net/10230/27951
http://dx.doi.org/10.1017/S1351324915000285
Access Level:acceso embargado
Palabra clave:Processament del llenguatge natural
Tractament del llenguatge natural (Informàtica)
Lingüística computacional
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spelling Data-driven deep-syntactic dependency parsingBallesteros, MiguelBohnet, BerndMille, SimonWanner, LeoProcessament del llenguatge naturalTractament del llenguatge natural (Informàtica)Lingüística computacional‘Deep-syntactic’ dependency structures that capture the argumentative, attributive and co-/nordinative relations between full words of a sentence have a great potential for a number/nof NLP-applications. The abstraction degree of these structures is in between the output/nof a syntactic dependency parser (connected trees defined over all words of a sentence and/nlanguage-specific grammatical functions) and the output of a semantic parser (forests of trees/ndefined over individual lexemes or phrasal chunks and abstract semantic role labels which/ncapture the frame structures of predicative elements and drop all attributive and coordinative/ndependencies). We propose a parser that provides deep-syntactic structures. The parser has/nbeen tested on Spanish, English and ChineseThe work reported on in this paper has been partially funded by the European Commission under the contract numbers FP7-ICT-610411 (MULTISENSOR) and H2020-645012-RIA (KRISTINA).Cambridge University Press201720172016info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/27951http://dx.doi.org/10.1017/S1351324915000285reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésNatural Language Engineering. 2016 Nov;22(6):939-74.info:eu-repo/grantAgreement/EC/FP7/610411info:eu-repo/grantAgreement/EC/H2020/645012© Cambridge University Press. The published version of the article: Ballesteros M, Bohnet B, Mille S, Wanner L. Data-driven deep-syntactic dependency parsing. Nat Lang Eng. 2016 Nov;22(6):939-74. http://dx.doi.org/10.1017/S1351324915000285info:eu-repo/semantics/embargoedAccessoai:repositori.upf.edu:10230/279512026-06-12T07:21:37Z
dc.title.none.fl_str_mv Data-driven deep-syntactic dependency parsing
title Data-driven deep-syntactic dependency parsing
spellingShingle Data-driven deep-syntactic dependency parsing
Ballesteros, Miguel
Processament del llenguatge natural
Tractament del llenguatge natural (Informàtica)
Lingüística computacional
title_short Data-driven deep-syntactic dependency parsing
title_full Data-driven deep-syntactic dependency parsing
title_fullStr Data-driven deep-syntactic dependency parsing
title_full_unstemmed Data-driven deep-syntactic dependency parsing
title_sort Data-driven deep-syntactic dependency parsing
dc.creator.none.fl_str_mv Ballesteros, Miguel
Bohnet, Bernd
Mille, Simon
Wanner, Leo
author Ballesteros, Miguel
author_facet Ballesteros, Miguel
Bohnet, Bernd
Mille, Simon
Wanner, Leo
author_role author
author2 Bohnet, Bernd
Mille, Simon
Wanner, Leo
author2_role author
author
author
dc.subject.none.fl_str_mv Processament del llenguatge natural
Tractament del llenguatge natural (Informàtica)
Lingüística computacional
topic Processament del llenguatge natural
Tractament del llenguatge natural (Informàtica)
Lingüística computacional
description ‘Deep-syntactic’ dependency structures that capture the argumentative, attributive and co-/nordinative relations between full words of a sentence have a great potential for a number/nof NLP-applications. The abstraction degree of these structures is in between the output/nof a syntactic dependency parser (connected trees defined over all words of a sentence and/nlanguage-specific grammatical functions) and the output of a semantic parser (forests of trees/ndefined over individual lexemes or phrasal chunks and abstract semantic role labels which/ncapture the frame structures of predicative elements and drop all attributive and coordinative/ndependencies). We propose a parser that provides deep-syntactic structures. The parser has/nbeen tested on Spanish, English and Chinese
publishDate 2016
dc.date.none.fl_str_mv 2016
2017
2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/27951
http://dx.doi.org/10.1017/S1351324915000285
url http://hdl.handle.net/10230/27951
http://dx.doi.org/10.1017/S1351324915000285
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Natural Language Engineering. 2016 Nov;22(6):939-74.
info:eu-repo/grantAgreement/EC/FP7/610411
info:eu-repo/grantAgreement/EC/H2020/645012
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cambridge University Press
publisher.none.fl_str_mv Cambridge University Press
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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