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Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography

Cilt: 5 Sayı: 2 30 Aralık 2025
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Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography

Öz

This paper presents a comparative analysis between human translation and automated outputs within the field of Turkish-Italian lexicography. Using a corpus of example sentences extracted from Turklex—a developing online multilingual dictionary—translations were carried out manually by a professional translator and subsequently generated by four different machine translation tools: Google Translate, DeepL, Gemini, and ChatGPT-4. Particular attention is paid to the rendering of headwords, a critical element in lexicographic accuracy. By examining the divergences and overlaps across these translations, the study highlights the strengths and limitations of current NMTs and AI-driven chatbots when applied to a less commonly examined language pair. To the best of our knowledge, this is the first focused investigation into Turkish-Italian translation within a lexicographical framework. The findings aim to inform both the evaluation of machine translation tools and the broader discussion on their integration into language resource development. The research found that while ChatGPT slightly outperformed the other tools, AI chatbots and NMTs still fall short of human translators in delivering translations that are both contextually nuanced and semantically accurate.

Anahtar Kelimeler

Proje Numarası

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Kaynakça

  1. Agung, I G.A. M., Putu G. B., & Nil Wayan, S. (2024). Translation performance of Google Translate and DeepL in translating Indonesian short stories into English. In Proceedings: Linguistics, Literature, Culture and Arts International Seminar (LITERATES), 178-185.
  2. Al R, Rafat, R. J., & Malkawi, M. (2025). ChatGPT translation vs. human translation: an examination of a literary text. Cogent Social Sciences, 11 (1), 1-21. DOI: 10.1080/23311886.2025.2472916.
  3. Banerjee, S., & Lavie, A. (2025). METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In Proceedings of the ACL workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization, 65-72.
  4. Bergenholtz, H., & Gouws, R. H. (2012). What is Lexicography?, Lexikos, 22, 31-42.
  5. Bernardini, S., & Zanettin, F. (2020). When corpora meet translation: A resource for teaching, research and practice. In C. O’Brien & M. Winters (Eds.), The Routledge Handbook of Translation and Technology (pp. 383–398). London: Routledge.
  6. Callison-Burch, C., Osborne, M., & Koehn, P. (2006). Re-evaluating the role of BLEU in machine translation research. In D. McCarthy, S. Wintener (Eds.), 11th Conference of the European Chapter of the Association for Computational Linguistics, Association for Cimputational Linguistics, 249-256. ChatGPT. Available from: https://chatgpt.com (February 2025).
  7. Çetin, Ö., & Duran, A. (2024). A Comparative Analysis Of The Performances Of Chatgpt, Deepl, Google Translate And A Human Translator In Community Based Settings, Amasya Üniversitesi Sosyal Bilimler Dergisi (ASOBİD), 9 (15), 120-173.
  8. de Schryver, G.M. (2023). Generative AI and Lexicography: The Current State of the Art Using ChatGPT, International Journal of Lexicography, XX, 1-33, https://doi.org/10.1093/ijl/ecad02. DeepL Translator. Available from: https://www.deepl.com/it/translator (February 2025).

Ayrıntılar

Birincil Dil

İngilizce

Konular

Çeviri ve Yorum Çalışmaları, Uygulamalı Dilbilim ve Eğitim Dilbilimi

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

30 Aralık 2025

Gönderilme Tarihi

20 Haziran 2025

Kabul Tarihi

1 Aralık 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 5 Sayı: 2

Kaynak Göster

APA
Patat, E. (2025). Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography. Uluslararası Dil ve Çeviri Çalışmaları Dergisi, 5(2), 281-307. https://doi.org/10.63673/Lotus.1723648
AMA
1.Patat E. Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography. LOTUS. 2025;5(2):281-307. doi:10.63673/Lotus.1723648
Chicago
Patat, Ellen. 2025. “Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography”. Uluslararası Dil ve Çeviri Çalışmaları Dergisi 5 (2): 281-307. https://doi.org/10.63673/Lotus.1723648.
EndNote
Patat E (01 Aralık 2025) Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography. Uluslararası Dil ve Çeviri Çalışmaları Dergisi 5 2 281–307.
IEEE
[1]E. Patat, “Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography”, LOTUS, c. 5, sy 2, ss. 281–307, Ara. 2025, doi: 10.63673/Lotus.1723648.
ISNAD
Patat, Ellen. “Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography”. Uluslararası Dil ve Çeviri Çalışmaları Dergisi 5/2 (01 Aralık 2025): 281-307. https://doi.org/10.63673/Lotus.1723648.
JAMA
1.Patat E. Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography. LOTUS. 2025;5:281–307.
MLA
Patat, Ellen. “Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography”. Uluslararası Dil ve Çeviri Çalışmaları Dergisi, c. 5, sy 2, Aralık 2025, ss. 281-07, doi:10.63673/Lotus.1723648.
Vancouver
1.Ellen Patat. Human Translator vs Machine Translation. A Case Study in Turkish-Italian Lexicography. LOTUS. 01 Aralık 2025;5(2):281-307. doi:10.63673/Lotus.1723648

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