publication . Article . Preprint . 2017

Deep encoding of etymological information in TEI

Jack Bowers; Laurent Romary;
Open Access English
  • Published: 07 Aug 2017
  • Publisher: HAL CCSD
  • Country: France
In this paper we provide a systematic and comprehensive set of modeling principles for representing etymological data in digital dictionaries using TEI. The purpose is to integrate in one coherent framework both digital representations of legacy dictionaries and born-digital lexical databases that are constructed manually or semi-automatically. We provide examples from many different types of etymological phenomena from traditional lexicographic practice, as well as analytical approaches from functional and cognitive linguistics such as metaphor, metonymy, and grammaticalization, which in many lexicographical and formal linguistic circles have not often been treated as truly etymological in nature, and have thus been largely left out of etymological dictionaries. In order to fully and accurately express the phenomena and their structures, we have made several proposals for expanding and amending some aspects of the existing TEI framework. Finally, with reference to both synchronic and diachronic data, we also demonstrate how encoders may integrate semantic web/linked open data information resources into TEI dictionaries as a basis for the sense, and/or the semantic domain, of an entry and/or an etymon.
Persistent Identifiers
free text keywords: TEI, dictionary, etymology, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], [SHS.LANGUE]Humanities and Social Sciences/Linguistics, Computer software, QA76.75-76.765, Computer Science - Computation and Language, TEI, dictionary, etymology, Encoding (semiotics), Representation language, Representation (arts), Focus (linguistics), Tracing, Natural language processing, computer.software_genre, computer, Variety (linguistics), Set (abstract data type), Artificial intelligence, business.industry, business, Computer science
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Funded by
Pooling Activities, Resources and Tools for Heritage E-research Networking, Optimization and Synergies
  • Funder: European Commission (EC)
  • Project Code: 654119
  • Funding stream: H2020 | RIA
2 research outcomes, page 1 of 1
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