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Linguistic evaluation of support verb constructions by OpenLogos and google translate

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Resumo:This paper presents a systematic human evaluation of translations of English support verb constructions produced by a rule-based machine translation (RBMT) system (OpenLogos) and a statistical machine translation (SMT) system (Google Translate) for five languages: French, German, Italian, Portuguese and Spanish. We classify support verb constructions by means of their syntactic structure and semantic behavior and present a qualitative analysis of their translation errors. The study aims to verify how machine translation (MT) systems translate fine-grained linguistic phenomena, and how well-equipped they are to produce high-quality translation. Another goal of the linguistically motivated quality analysis of SVC raw output is to reinforce the need for better system hybridization, which leverages the strengths of RBMT to the benefit of SMT, especially in improving the translation of multiword units. Taking multiword units into account, we propose an effective method to achieve MT hybridization based on the integration of semantico-syntactic knowledge into SMT.
Autores principais:Barreiro, A.
Outros Autores:Monti, J.; Orliac, B.; Preuß, S.; Arrieta, K.; Ling, W.; Batista, F.; Trancoso, I.
Assunto:Machine translation MT evaluation Support verb constructions Multiword units Semantico-syntactic knowledge MT hybridization
Ano:2014
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:ISCTE
Idioma:inglês
Origem:Repositório ISCTE

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