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Journal of the Text Encoding Initiative
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Journal of the Text Encoding Initiative
Article . 2016 . Peer-reviewed
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Deep Encoding of Etymological Information in TEI

Authors: Jack Bowers; Laurent Romary;

Deep Encoding of Etymological Information in TEI

Abstract

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.

Country
France
Subjects by Vocabulary

Microsoft Academic Graph classification: business.industry Computer science Representation (arts) Tracing computer.software_genre Variety (linguistics) Focus (linguistics) Set (abstract data type) Representation language Encoding (semiotics) Artificial intelligence business computer Natural language processing

Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, etymology, General Medicine, TEI, [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], QA76.75-76.765, Computer software, [SHS.LANGUE]Humanities and Social Sciences/Linguistics, Computation and Language (cs.CL), dictionary

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    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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