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

Khan, Anas Fahad; Chiarcos, Christian; Declerck, Thierry; Gîfu, Daniela; García, Elena González-Blanco; Gracia, Jorge; Ionov, Maxim; Labropoulou, Penny; Mambrini, Francesco; McCrae, John P.; Pagé-Perron, Émilie; Passarotti, Marco; Ros, Salvador; Truică, Ciprian-Octavian

doi:10.3233/sw-222859

Cited by 7 publications

(6 citation statements)

References 95 publications

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“…Our goal was to generate a dataset with all dictionary forms (known as canonical forms or lemmas) that can be adopted by projects dealing with the lemmatization of Latin, independently from the particular strategies adopted by each project. We wanted to provide each lemma with a stable Uniform Resource Identifier (URI) and to model its linguistic properties with the help of OWL ontologies for Linguistic Linked Open Data (LOD) (Khan et al, 2022).…”

Section: Methods Stepsmentioning

confidence: 99%

The LiLa Lemma Bank: A Knowledge Base of Latin Canonical Forms

Mambrini,

Passarotti

2023

Journal of Open Humanities Data

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The dataset contains a list of 215,102 Latin dictionary forms (known as canonical forms or lemmas). The dataset is a set of 1,699,687 Resource Description Framework (RDF) triples that describe, using a series of Web Ontology Language (OWL) ontologies for Linguistic Linked Data, the morphological properties of these forms. The dataset is used to link together a series of corpora and dictionaries in the interoperable network of language resources published by the LiLa: Linking Latin project.

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Section: Methods Stepsmentioning

confidence: 99%

The LiLa Lemma Bank: A Knowledge Base of Latin Canonical Forms

Mambrini,

Passarotti

2023

Journal of Open Humanities Data

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“…OntoLex-Lemon, McCrae et al (2017), allows the modeling and publishing of lexical resources on the Semantic Web, Khan et al (2022). In particular, it provides support for enriching ontologies with linguistic information, by modeling, for instance, the different meanings a word can denote.…”

Section: Related Workmentioning

confidence: 99%

Linked Data Semantic Distance with Global Normalization for evaluating Semantic Similarity in a Taxonomy

Formica,

Taglino

2023

CEAI

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In this work, the problem of evaluating semantic similarity in a taxonomy by relying on the notion of information content is investigated. In particular, a measure that takes into account not only the generic sense of a concept but also its intended sense in a given context is considered. Such a measure needs a semantic relatedness approach in order to evaluate the relatedness between the generic sense and the intended sense of a concept. In this work, we show that relying on the Linked Data Semantic Distance with Global Normalization leads to higher Spearman's correlation values with human judgment with respect to the original proposal and previous experiments of the authors.

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“…Datasets describing semantic change would therefore seem ideal candidates for modelling as linked data and publication on the Semantic Web, since the Semantic Web is particularly suited for the integration of heterogeneous data in a standardised, highly interoperable way. Moreover, the Semantic Web has had a strong emphasis on ontological resources since its beginnings, as well as a more recent focus on the provision of lexical data (witness the recent popularity of OntoLex-Lemon; further details on the use of linked data models for linguistic data can be found in Khan et al 2022). The integration of heterogeneous datasets in the Semantic Web takes place at different levels, but in the first place it should occur at a semantic level, that is, on the basis of the meaning of the data itself.…”

Section: Introductionmentioning

confidence: 99%

Toward a Representation of Semantic Change in Linked Data

Khan,

Frontini

2024

Languages

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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.

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

Cited by 7 publications

References 95 publications

The LiLa Lemma Bank: A Knowledge Base of Latin Canonical Forms

The LiLa Lemma Bank: A Knowledge Base of Latin Canonical Forms

Linked Data Semantic Distance with Global Normalization for evaluating Semantic Similarity in a Taxonomy

Toward a Representation of Semantic Change in Linked Data

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