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1
Utilising knowledge graph embeddings for data-to-text generation
Arcan, Mihael; Pasricha, Nivranshu; Buitelaar, Paul. - : Association for Computational Linguistics, 2021
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2
NUIG-DSI’s submission to the GEM Benchmark 2021
Buitelaar, Paul; Arcan, Mihael; Pasricha, Nivranshu. - : Association for Computational Linguistics, 2021
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3
Enhancing multiple-choice question answering with causal knowledge
Buitelaar, Paul; Dalal, Dhairya; Arcan, Mihael. - : Association for Computational Linguistics, 2021
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4
NUIG-DSI at the WebNLG+ challenge: Leveraging transfer learning for RDF-to-text generation
Pasricha, Nivranshu; Arcan, Mihael; Buitelaar, Paul. - : Association for Computational Linguistics, 2021
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5
Bilingual lexicon induction across orthographically-distinct under-resourced Dravidian languages
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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6
Leveraging orthographic information to improve machine translation of under-resourced languages
Asoka Chakravarthi, Bharathi Raja. - : NUI Galway, 2020
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7
NUIG at TIAD: Combining unsupervised NLP and graph metrics for translation inference
Arcan, Mihael; McCrae, John P.. - : European Language Resources Association (ELRA), 2020
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8
Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios ...
Abstract: Rule-based machine translation is a machine translation paradigm where linguistic knowledge is encoded by an expert in the form of rules that translate text from source to target language. While this approach grants extensive control over the output of the system, the cost of formalising the needed linguistic knowledge is much higher than training a corpus-based system, where a machine learning approach is used to automatically learn to translate from examples. In this paper, we describe different approaches to leverage the information contained in rule-based machine translation systems to improve a corpus-based one, namely, a neural machine translation model, with a focus on a low-resource scenario. Three different kinds of information were used: morphological information, named entities and terminology. In addition to evaluating the general performance of the system, we systematically analysed the performance of the proposed approaches when dealing with the targeted phenomena. Our results suggest that the ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2009.13398
https://dx.doi.org/10.48550/arxiv.2009.13398
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9
Bilingual Lexicon Induction across Orthographically-distinct Under-Resourced Dravidian Languages ...
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10
Bilingual Lexicon Induction across Orthographically-distinct Under-Resourced Dravidian Languages ...
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11
Comparison of Different Orthographies for Machine Translation of Under-Resourced Dravidian Languages
Chakravarthi, Bharathi Raja; Arcan, Mihael; McCrae, John P.. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2019. : OASIcs - OpenAccess Series in Informatics. 2nd Conference on Language, Data and Knowledge (LDK 2019), 2019
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12
TIAD 2019 Shared Task: Leveraging knowledge graphs with neural machine translation for automatic multilingual dictionary generation
McCrae, John P.; Ahmadi, Sina; Torregrosa, Daniel. - : National University of Ireland, Galway, 2019
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13
The ESSOT system goes wild: an easy way for translating ontologies
Arcan, Mihael; Dragoni, Mauro; Buitelaar, Paul. - : CEUR-WS.org, 2019
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14
OTTO - ontology translation system
Arcan, Mihael; Asooja, Kartik; Ziad, Housam. - : CEUR-WS.org, 2019
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15
Experiments with term translation
Arcan, Mihael; Buitelaar, Paul; Federmann, Christian. - : Association for Computational Linguistics, 2019
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16
Ontology label translation
Buitelaar, Paul; Arcan, Mihael. - : Association for Computational Linguistics, 2019
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17
Generating linked-data based domain-specific sentiment lexicons from legacy language and semantic resources
Vulcu, Gabriela; Buitelaar, Paul; Pereira, Bianca. - : European Language Resources Association, 2019
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18
Automatic enrichment of terminological resources: the IATE RDF example
McCrae, John P.; Montiel-Ponsoda, Elena; Buitelaar, Paul. - : European Language Resources Association, 2019
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19
Avtomatsko pridobivanje besednih zvez iz korpusa z uporabo leksikona SSJ
Arcan, Mihael; Arhar Holdt, Špela. - : Centre for Slovene as a Second and Foreign Language, Univerity of Ljubljana, 2019
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20
Inferring translation candidates for multilingual dictionary generation with multi-way neural machine translation
Arcan, Mihael; McCrae, John P.; Torregrosa, Daniel. - : National University of Ireland, Galway, 2019
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