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Utilising knowledge graph embeddings for data-to-text generation
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Enhancing multiple-choice question answering with causal knowledge
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NUIG-DSI at the WebNLG+ challenge: Leveraging transfer learning for RDF-to-text generation
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Bilingual lexicon induction across orthographically-distinct under-resourced Dravidian languages
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In: Chakravarthi, Bharathi Raja orcid:0000-0002-4575-7934 , Rajasekaran, Navaneethan, Arcan, Mihael orcid:0000-0002-3116-621X , McGuinness, Kevin orcid:0000-0003-1336-6477 , O'Connor, Noel E. orcid:0000-0002-4033-9135 and McCrae, John P. orcid:0000-0002-7227-1331 (2020) Bilingual lexicon induction across orthographically-distinct under-resourced Dravidian languages. In: 7th Workshop on NLP for Similar Languages, Varieties and Dialects, 13 Dec 2020, Barcelona, Spain (Online). (2020)
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Leveraging orthographic information to improve machine translation of under-resourced languages
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NUIG at TIAD: Combining unsupervised NLP and graph metrics for translation inference
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Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios ...
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Bilingual Lexicon Induction across Orthographically-distinct Under-Resourced Dravidian Languages ...
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Bilingual Lexicon Induction across Orthographically-distinct Under-Resourced Dravidian Languages ...
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Comparison of Different Orthographies for Machine Translation of Under-Resourced Dravidian Languages
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TIAD 2019 Shared Task: Leveraging knowledge graphs with neural machine translation for automatic multilingual dictionary generation
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The ESSOT system goes wild: an easy way for translating ontologies
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Experiments with term translation
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Abstract:
In this article we investigate the translation of financial terms from English into German in the isolation of an ontology vocabulary. For this study we automatically built new domain-specific resources from the translation search engine Linguee and from the online encyclopaedia Wikipedia. Due to the fact that we performed the translation approach on a monolingual ontology, we ran several sub-experiments to find the most appropriate model to translate the financial vocabulary. The findings from these experiments lead to the conclusion that a hybrid translation system, a combination of bilingual terminological resources and statistical machine translation, can help to improve translation of domain-specific terms. Finally we undertook a manual cross-lingual evaluation on the monolingual ontology to get a better understanding on this specific short text translation task. ; This work has been funded under the Seventh Framework Programme for Research and Technological Development of the European Commission through the T4ME contract (grant agreement no.: 249119) and in part by the European Union under Grant No. 248458 for the Monnet project as well as by the Science Foundation Ireland under Grant No. SFI/08/CE/I1380 (Lion-2). The authors would like to thank Noëmi Aepli, Tobias Wunner and Thierry Declerck for their help with the manual evaluation. We are grateful to the anonymous reviewers for their valuable feedback. ; non-peer-reviewed
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Keyword:
Empirical machine translation; Ontologies and terminology
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URL: http://hdl.handle.net/10379/14933
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Generating linked-data based domain-specific sentiment lexicons from legacy language and semantic resources
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Automatic enrichment of terminological resources: the IATE RDF example
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Avtomatsko pridobivanje besednih zvez iz korpusa z uporabo leksikona SSJ
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Inferring translation candidates for multilingual dictionary generation with multi-way neural machine translation
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