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Language Technologies For A Multilingual Europe: Tc3 Iii ...
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Language Technologies For A Multilingual Europe: Tc3 Iii ...
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Improving Machine Translation through Linked Data
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In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 355-366 (2017) (2017)
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Abstract:
With the ever increasing availability of linked multilingual lexical resources, there is a renewed interest in extending Natural Language Processing (NLP) applications so that they can make use of the vast set of lexical knowledge bases available in the Semantic Web. In the case of Machine Translation, MT systems can potentially benefit from such a resource. Unknown words and ambiguous translations are among the most common sources of error. In this paper, we attempt to minimise these types of errors by interfacing Statistical Machine Translation (SMT) models with Linked Open Data (LOD) resources such as DBpedia and BabelNet. We perform several experiments based on the SMT system Moses and evaluate multiple strategies for exploiting knowledge from multilingual linked data in automatically translating named entities. We conclude with an analysis of best practices for multilingual linked data sets in order to optimise their benefit to multilingual and cross-lingual applications.
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Keyword:
Computational linguistics. Natural language processing; P98-98.5
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URL: https://doaj.org/article/4db0865eb94a45158a905a973db8172f https://doi.org/10.1515/pralin-2017-0033
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Language technologies for a multilingual Europe
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In: Language Science Press; (2016)
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Language technologies for a multilingual Europe
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In: Language Science Press; (2016)
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Language technologies for a multilingual Europe
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In: Language Science Press; (2016)
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Language technologies for a multilingual Europe
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In: Language Science Press; (2016)
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Language technologies for a multilingual Europe
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In: Language Science Press; (2016)
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Language technologies for a multilingual Europe
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In: Language Science Press; (2016)
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