Models to represent linguistic linked data

Bosque-Gil, J. ; Gracia, J. (Universidad de Zaragoza) ; Montiel-Ponsoda, E. ; Gómez-Pérez, A.

Resumen: As the interest of the Semantic Web and computational linguistics communities in linguistic linked data (LLD) keeps increasing and the number of contributions that dwell on LLD rapidly grows, scholars (and linguists in particular) interested in the development of LLD resources sometimes find it difficult to determine which mechanism is suitable for their needs and which challenges have already been addressed. This review seeks to present the state of the art on the models, ontologies and their extensions to represent language resources as LLD by focusing on the nature of the linguistic content they aim to encode. Four basic groups of models are distinguished in this work: models to represent the main elements of lexical resources (group 1), vocabularies developed as extensions to models in group 1 and ontologies that provide more granularity on specific levels of linguistic analysis (group 2), catalogues of linguistic data categories (group 3) and other models such as corpora models or service-oriented ones (group 4). Contributions encompassed in these four groups are described, highlighting their reuse by the community and the modelling challenges that are still to be faced.

Idioma: Inglés

DOI: 10.1017/S1351324918000347

Año: 2018

Publicado en: NATURAL LANGUAGE ENGINEERING 24, 6 (2018), 811-859
ISSN: 1351-3249

Factor impacto JCR: 1.13 (2018)

Categ. JCR: LINGUISTICS rank: 68 / 182 = 0.374 (2018) - Q2 - T2
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 103 / 133 = 0.774 (2018) - Q4 - T3

Factor impacto SCIMAGO: 0.315 - Artificial Intelligence (Q2) - Software (Q2) - Linguistics and Language (Q2) - Language and Linguistics (Q2)

Financiación: info:eu-repo/grantAgreement/ES/MEC-MINECO/TIN2013-46238-C4-2-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2015-68955-REDT

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)