Models to represent linguistic linked data

Abstract

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.

MMoOn Core – the Multilingual Morpheme Ontology

“…been presented at various scientific events to gain feedback from the target user groups which has been considered and integrated into the final publication state of MMoOn Core as well. Despite this longstanding process from conceptualizing to actually publishing this accompanying article for the MMoOn Core ontology, no comparable advancement in creating a domain ontology for representing MLD is recorded [6].…”

“…Since then a significant rise of language data on the Semantic Web emerged. Academic, industrial and technological interest into Linguistic Linked Data appeared and materialized in three areas: (1) W3C community groups such as Linked Data for Language Technology (LD4LT) 1 or BPMLOD, 2 and (2) European research projects such as LIDER, 3 Falcon 4 or FREME 5 as well as (3) scientific workshops and special issues such as the workshop series on Linked Data in Linguistics, 6 the Multilingual Semantic Web workshop series 7 or the special issue of the Semantic Web Journal on Multilingual Linked Open Data [27]. 8 A cross-disciplinary usage of LLOD has already been proven to be achievable in the case of the OntoLex-lemon model 9 [40] which successfully unified linguistic and NLP research data for lexical language data (LLD).…”

“…However, a similar approach for MLD is not yet established. While a plethora of linguistic resources 10 for the LLD domain exists and is highly reused, there is still a great gap for equivalent morphological datasets and ontologies [6,27]. There-fore, the aim of this paper is to present the Multilingual Morpheme Ontology, in short MMoOn Core.…”

When linguistics meets web technologies. Recent advances in modelling linguistic linked data

“…Moreover, thanks to the use of a shared data model with a powerful native linking mechanism, LLD datasets can easily be integrated with, and therefore enriched by, linked data datasets belonging to other domains, for instance, geographical and historical datasets or gazetteers and authority lists. Indeed, OWL vocabularies, such as PROV-O, 8 make it straightforward to add complex, structured information describing when something happened or to make hypotheses explicit 9 -all of which contributes towards the creation of ever richer and more machine actionable metadata for linked data language resources.…”

Rutas de acceso al léxico en un entorno lexicográfico

“…Entre los modelos más conocidos, que dan cuenta de los diferentes niveles lingüísticos, están LMF, TEI, SKOS y Ontolex-lemon, que, además, ha elaborado recientemente un modelo para fines lexicográficos (cf. Bosque-Gil et al, 2018. En Vila-Suero et al (2014) se explican los pasos para la publicación de los recursos como datos enlazados.…”