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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Detalhes bibliográficos
Autores: Ballesteros, Miguel, Bohnet, Bernd, Mille, Simon, Wanner, Leo
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2016
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/27951
Acesso em linha:http://hdl.handle.net/10230/27951
http://dx.doi.org/10.1017/S1351324915000285
Access Level:acceso embargado
Palavra-chave:Processament del llenguatge natural
Tractament del llenguatge natural (Informàtica)
Lingüística computacional
Descrição
Resumo:‘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