LL(O)D and NLP perspectives on semantic change for humanities research

Armaselu, Florentina; Apostol, Elena-Simona; Khan, Anas Fahad; Liebeskind, Chaya; McGillivray, Barbara; Truică, Ciprian-Octavian; Utka, Andrius; Oleškevičienė, Giedrė Valūnaitė; Erp, Marieke van

doi:10.3233/sw-222848

Cited by 7 publications

(4 citation statements)

References 124 publications

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“…It is important to recall that in order to compute the 28 tables, one for each pair of the M &C dataset, each table containing 28 possible contexts for that pair, a disambiguation step has to be performed. In fact, it is wellknown that in Wikipedia, and consequently in DBpedia, terms are addressed with the possible meanings they have, i.e., a term is associated with multiple senses due to, for instance, semantic change or shift, Armaselu et al (2022), Montariol et al (2021). For this reason, in the experiment, the disambiguation is necessary in order to address senses in line with the HJ evaluation in the M &C experiment.…”

Section: Resultsmentioning

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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Section: Resultsmentioning

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 recent years, Natural Language Processing researchers have developed algorithms that predict lexical semantic change (Schlechtweg et al 2020). Moreover, annotated texts provide valuable context for word meanings, and some researchers have proposed models that represent semantic change information contained in lexical resources like dictionaries as linked data (Armaselu et al 2022). However, accessing resources and tools for semantic change research remains challenging due to fragmentation across various domains.…”

Section: Contextmentioning

confidence: 99%

Multilingual Workflows for Semantic Change Research

Marongiu,

McGillivray,

Khan

2024

Journal of Open Humanities Data

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We present a series of workflows that aim to support research in lexical semantic change, i.e. the phenomenon by which words change their meaning over time. The workflows each consist of a series of steps required to detect words that have undergone semantic change as evidenced by a corpus and cover a range of user scenarios, including lexicology, historical research, and legal studies. The workflows were created following the model adopted by the Social Sciences and Humanities Open MarketPlace and were designed in the context of a project on CLARIN resource families supported by CLARIN ERIC. In this paper, we present a use case for the workflow on lexicology, referring to resources for Latin and ancient Greek.

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“…The authors propose an OWL ontology to formalize a scheme that combines ISO standards describing discourse relations and dialogue acts. Armaselu et al [7] propose an approach based on word embeddings and LLOD resources to trace the evolution of concepts in different languages and historical periods. McGillivray et al [171] similarly address the issue of diachronic semantic search by integrating Latin corpus data, Latin WordNet, and Wikidata into a graph database.…”

Section: Etymology and Diachronicitymentioning

confidence: 99%

Multilinguality and LLOD: A survey across linguistic description levels

Gromann,

Apostol,

Chiarcos

et al. 2024

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Limited accessibility to language resources and technologies represents a challenge for the analysis, preservation, and documentation of natural languages other than English. Linguistic Linked (Open) Data (LLOD) holds the promise to ease the creation, linking, and reuse of multilingual linguistic data across distributed and heterogeneous resources. However, individual language resources and technologies accommodate or target different linguistic description levels, e.g., morphology, syntax, phonology, and pragmatics. In this comprehensive survey, the state-of-the-art of multilinguality and LLOD is being represented with a particular focus on linguistic description levels, identifying open challenges and gaps as well as proposing an ideal ecosystem for multilingual LLOD across description levels. This survey seeks to contribute an introductory text for newcomers to the field of multilingual LLOD, uncover gaps and challenges to be tackled by the LLOD community in reference to linguistic description levels, and present a solid basis for a future best practice of multilingual LLOD across description levels.

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LL(O)D and NLP perspectives on semantic change for humanities research

Cited by 7 publications

References 124 publications

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

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

Multilingual Workflows for Semantic Change Research

Multilinguality and LLOD: A survey across linguistic description levels

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