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Conference Papers Year : 2024

On Modelling Corpus Citations in Computational Lexical Resources

Abstract

In this article we look at how two different standards for lexical resources, TEI and OntoLex, deal with corpus citations in lexicons. We will focus on how corpus citations in retrodigitised dictionaries can be modelled using each of the two standards since this provides us with a suitably challenging use case. After looking at the structure of an example entry from a legacy dictionary, we examine the two approaches offered by the two different standards by outlining an encoding for the example entry using both of them (note that this article features the first extended discussion of how the Frequency Attestation and Corpus (FrAC) module of OntoLex deals with citations). After comparing the two approaches and looking at the advantages and disadvantages of both, we argue for a combination of both. In the last part of the article we discuss different ways of doing this, giving our preference for a strategy which makes use of RDFa.
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Dates and versions

hal-04535091 , version 1 (05-04-2024)

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  • HAL Id : hal-04535091 , version 1

Cite

Anas Fahad Khan, Maxim Ionov, Christian Chiarcos, Laurent Romary, Gilles Serasset, et al.. On Modelling Corpus Citations in Computational Lexical Resources. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ELDA; ICCL, May 2024, Turin, Italy. pp.12385--12394. ⟨hal-04535091⟩
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