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In:Recent Advances in Multiword Units in Machine Translation and Translation Technology
Edited by Johanna Monti, Gloria Corpas Pastor, Ruslan Mitkov and Carlos Manuel Hidalgo-Ternero
[Current Issues in Linguistic Theory 366] 2024
► pp. 40–56

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Chapter 3
Evaluating the Italian-English machine translation quality of MWUs in the domain of archaeology

 | University of Naples “L’Orientale”, UNIOR NLP Research Group
 | University of Naples “L’Orientale”, UNIOR NLP Research Group
Published online: 7 November 2024
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https://doi.org/10.1075/cilt.366.03spe
Abstract
Multiword units (MWUs) represent a challenging and problematic linguistic issue in the field of Natural Language Processing (NLP) due to their idiosyncratic nature. This paper investigates the quality of Neural Machine Translation (NMT) outputs when dealing with MWUs in the domain of archaeology. As a case study, a dataset of 100 MWUs is used as a Gold Standard to evaluate out-of-context and in-context translation outputs from three state-of-the-art NMT systems for the Italian-English language pair: Google Translate, DeepL, and Microsoft Bing Translator. MT outputs are manually evaluated with reference to the Gold Standard, namely out-of-context and in-context human English translations of the selected 100 MWUs. Results show that terminology is still a problematic category for MT quality and that MWUs translation may vary, and sometimes even improve, when further context is provided.
Article outline
  • 1.Introduction
  • 2.Related work
    • 2.1Terminology translation
    • 2.2Terminology translation evaluation
  • 3.Experimental setup
    • 3.1The dataset
    • 3.2The evaluation methodology
    • 3.3Global evaluation
    • 3.4Local error analysis
  • 4.Conclusions
  • Notes
  • References
References (26)
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