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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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Abstract:
This paper describes the system submitted by NUIG-DSI to the WebNLG+ challenge 2020 in the RDF-to-text generation task for the English language. For this challenge, we leverage transfer learning by adopting the T5 model architecture for our submission and fine-tune the model on the WebNLG+ corpus. Our submission ranks among the top five systems for most of the automatic evaluation metrics achieving a BLEU score of 51.74 over all categories with scores of 58.23 and 45.57 across seen and unseen categories respectively. ; This work was conducted with the financial support of the Science Foundation Ireland Centre for Research Training in Artificial Intelligence under Grant No. 18/CRT/6223 and co-supported by Science Foundation Ireland under grant number SFI/12/RC/2289 2 (Insight), co-funded by the European Regional Development Fund. ; peer-reviewed
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Keyword:
RDF-to-text generation; WebNLG
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URL: http://hdl.handle.net/10379/16525
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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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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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