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Journal Articles Journal of the Text Encoding Initiative Year : 2017

Deep encoding of etymological information in TEI

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Abstract

This paper aims to provide a comprehensive modeling and representation of etymological data in digital dictionaries. The purpose is to integrate in one coherent framework both digital representations of legacy dictionaries, and also born-digital lexical databases that are constructed manually or semi-automatically. We want to propose a systematic and coherent set of modeling principles for a variety of etymological phenomena that may contribute to the creation of a continuum between existing and future lexical constructs, where anyone interested in tracing the history of words and their meanings will be able to seamlessly query lexical resources. Instead of designing an ad hoc model and representation language for digital etymological data, we will focus on identifying all the possibilities offered by the TEI guidelines for the representation of lexical information.
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Dates and versions

hal-01296498 , version 1 (01-04-2016)
hal-01296498 , version 2 (30-11-2016)

Licence

Attribution - CC BY 4.0

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Cite

Jack Bowers, Laurent Romary. Deep encoding of etymological information in TEI. Journal of the Text Encoding Initiative, 2017, 10, ⟨10.4000/jtei.1643⟩. ⟨hal-01296498v2⟩
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