Converting Language Resources into Linked Data

2020 ◽  
pp. 163-180
Author(s):  
Philipp Cimiano ◽  
Christian Chiarcos ◽  
John P. McCrae ◽  
Jorge Gracia
Author(s):  
Gard B. Jenset ◽  
Barbara McGillivray

Chapter 5 covers the topic of language resources in historical linguistics. It explains the relationship between historical corpora and language resources in a data-driven framework, and refers to valency lexicons as an example. The chapter also points to resources external to the linguistics community, and shows how these can enrich the research process in historical linguistics. We explain the basic concepts of linked data, and argue for a more extensive linking of linguistic resources with other types of resources, including gazetteers and prosopographical data. We provide a worked example from the LexInfo ontology.


Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 274 ◽  
Author(s):  
Frances Gillis-Webber

The English-Xhosa Dictionary for Nurses (EXDN) is a bilingual, unidirectional printed dictionary in the public domain, with English and isiXhosa as the language pair. By extending the digitisation efforts of EXDN from a human-readable digital object to a machine-readable state, using Resource Description Framework (RDF) as the data model, semantically interoperable structured data can be created, thus enabling EXDN’s data to be reused, aggregated and integrated with other language resources, where it can serve as a potential aid in the development of future language resources for isiXhosa, an under-resourced language in South Africa. The methodological guidelines for the construction of a Linguistic Linked Data framework (LLDF) for a lexicographic resource, as applied to EXDN, are described, where an LLDF can be defined as a framework: (1) which describes data in RDF, (2) using a model designed for the representation of linguistic information, (3) which adheres to Linked Data principles, and (4) which supports versioning, allowing for change. The result is a bidirectional lexicographic resource, previously bounded and static, now unbounded and evolving, with the ability to extend to multilingualism.


2015 ◽  
Author(s):  
Benjamin Siemoneit ◽  
John Philip McCrae ◽  
Philipp Cimiano

Author(s):  
Jorge Gracia ◽  
Daniel Vila-Suero ◽  
John P. McCrae ◽  
Tiziano Flati ◽  
Ciro Baron ◽  
...  

2018 ◽  
Vol 24 (6) ◽  
pp. 811-859 ◽  
Author(s):  
J. BOSQUE-GIL ◽  
J. GRACIA ◽  
E. MONTIEL-PONSODA ◽  
A. GÓMEZ-PÉREZ

AbstractAs 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.


2010 ◽  
Author(s):  
Kartik Bhavsar ◽  
Reanna Poncheri Harman ◽  
Amber Harris ◽  
Kathryn Nelson ◽  
Eric A. Surface ◽  
...  

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