Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (3)

Search Parameters:
Keywords = ontolex-lemon

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
24 pages, 575 KB  
Article
Toward a Representation of Semantic Change in Linked Data
by Anas Fahad Khan and Francesca Frontini
Languages 2024, 9(6), 215; https://doi.org/10.3390/languages9060215 - 12 Jun 2024
Cited by 1 | Viewed by 3233
Abstract
In this article, we introduce a new framework, the Intensional–Ontological Model (IOM), for representing meaning, and especially for representing semantic change, in linguistic linked data resources. This framework, which makes use of previous work in the literature on lexical semantics and ontologies, is [...] Read more.
In this article, we introduce a new framework, the Intensional–Ontological Model (IOM), for representing meaning, and especially for representing semantic change, in linguistic linked data resources. This framework, which makes use of previous work in the literature on lexical semantics and ontologies, is intended to help clarify what we mean when we model semantic change and to assist in elaborating different ontology patterns for doing so. In this work, we assume a simple architecture, one which is at the basis of the well-known OntoLex-Lemon vocabulary and which consists of one or more lexicons linked to an ontology. Our model, which is based on this architecture and informed by previous work on word senses and ontologies, is intended to provide a clear interpretation for the modelling of both onomasiological and semiasological changes, in both static and dynamic versions. This article describes how the IOM framework represents word meaning as the relationship between a word and an ontological concepts in the ’static’ case, demonstrating that the IOM is compatible with OntoLex-Lemon (while at the same time providing a greater level of detail as to the meaning of the ’sense’ and ’reference’ relationships). It then goes on to detail how the IOM can help us understand how to model semantic shifts in linked data lexical resources with a focus on conceptual change and the addition of temporal information to semantic shift data. Full article
(This article belongs to the Special Issue Semantics and Meaning Representation)
Show Figures

Figure 1

17 pages, 1880 KB  
Article
Towards the Representation of Etymological Data on the Semantic Web
by Anas Fahad Khan
Information 2018, 9(12), 304; https://doi.org/10.3390/info9120304 - 30 Nov 2018
Cited by 23 | Viewed by 7483
Abstract
In this article, we look at the potential for a wide-coverage modelling of etymological information as linked data using the Resource Data Framework (RDF) data model. We begin with a discussion of some of the most typical features of etymological data and the [...] Read more.
In this article, we look at the potential for a wide-coverage modelling of etymological information as linked data using the Resource Data Framework (RDF) data model. We begin with a discussion of some of the most typical features of etymological data and the challenges that these might pose to an RDF-based modelling. We then propose a new vocabulary for representing etymological data, the Ontolex-lemon Etymological Extension (lemonETY), based on the ontolex-lemon model. Each of the main elements of our new model is motivated with reference to the preceding discussion. Full article
(This article belongs to the Special Issue Towards the Multilingual Web of Data)
Show Figures

Figure 1

30 pages, 2555 KB  
Article
Conversion of the English-Xhosa Dictionary for Nurses to a Linguistic Linked Data Framework
by Frances Gillis-Webber
Information 2018, 9(11), 274; https://doi.org/10.3390/info9110274 - 6 Nov 2018
Cited by 4 | Viewed by 5574
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Towards the Multilingual Web of Data)
Show Figures

Figure 1

Back to TopTop