The Automatic Determination of Translation Equivalents in Lexicography: What Works and What Doesn’t?

By December 19, 2024,
Page 305-317
Author Michaela Denisová, Gilles-Maurice de Schryver, Pavel Rychlý
Title The Automatic Determination of Translation Equivalents in Lexicography: What Works and What Doesn’t?
Abstract Cross-lingual embedding models act as facilitator of lexical knowledge transfer and offer many advantages, notably their applicability to low-resource and non-standard language pairs, making them a valuable tool for retrieving translation equivalents in lexicography. Despite their potential, these models have primarily been developed with a focus on Natural Language Processing (NLP), leading to significant issues, including flawed training and evaluation data, as well as inadequate evaluation metrics and procedures. In this paper, we introduce cross-lingual embedding models for lexicography, addressing the challenges and limitations inherent in the current NLP-focused research. We demonstrate the problematic aspects across three baseline cross-lingual embedding models and three language pairs and outline possible solutions. We show the importance of high-quality data, advocating that its role is vital compared to algorithmic optimisation in enhancing the effectiveness of these models.
Session Talk
Keywords translation equivalent determination; cross-lingual embedding models; evaluation
BibTex 
@inproceedings{euralex_2024_paper_24,
address = {Cavtat},
title = {The Automatic Determination of Translation Equivalents in Lexicography: What Works and What Doesn’t?},isbn = {978-953-7967-77-2},
shorttitle = {Euralex 2024},
url = {},
language = {eng},
booktitle = {Lexicography and Semantics. Proceedings of the XXI EURALEX International Congress},
publisher = {Institut za hrvatski jezik},
author = {Denisová, Michaela and de Schryver, Gilles-Maurice and Rychlý, Pavel},
editor = {Despot, Kristina Š. and Ostroški Anić, Ana and Brač, Ivana},
year = {2024},
pages = {305-317}
}
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