Modelling Etymology in LMF/TEI: The Grande Dicionário Houaiss da Língua Portuguesa Dictionary as a Use Case

Fahad Khan, Laurent Romary, Ana Salgado, Jack Bowers, Mohamed Khemakhem, Toma Tasovac

Abstract
In this article we will introduce two of the new parts of the new multi-part version of the Lexical Markup Framework (LMF) ISO standard, namely part 3 of the standard (ISO 24613-3), which deals with etymological and diachronic data, and Part 4 (ISO 24613-4), which consists of a TEI serialisation of all of the prior parts of the model. We will demonstrate the use of both standards by describing the LMF encoding of a small number of examples taken from a sample conversion of the reference Portuguese dictionary Grande Dicionário Houaiss da Língua Portuguesa, part of a broader experiment comprising the analysis of different, heterogeneously encoded, Portuguese lexical resources. We present the examples in the Unified Modelling Language (UML) and also in a couple of cases in TEI.
Anthology ID:
2020.lrec-1.388
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
3172–3180
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.388
DOI:
Bibkey:
Cite (ACL):
Fahad Khan, Laurent Romary, Ana Salgado, Jack Bowers, Mohamed Khemakhem, and Toma Tasovac. 2020. Modelling Etymology in LMF/TEI: The Grande Dicionário Houaiss da Língua Portuguesa Dictionary as a Use Case. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 3172–3180, Marseille, France. European Language Resources Association.
Cite (Informal):
Modelling Etymology in LMF/TEI: The Grande Dicionário Houaiss da Língua Portuguesa Dictionary as a Use Case (Khan et al., LREC 2020)
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