Impacte de la postedició automàtica i de les estratègies de prompting en les característiques lingüístiques de les traduccions editorials de l’anglès al francès

Autors/ores

  • Valentin Scourneau Polytechnic University of Hauts-de-France

Resum

Aquest article consisteix a comparar una traducció automàtica (TA) en brut i una postedició automàtica (PA). Es recupera la TA de tres sistemes (DeepL, Google Translate i GPT-4o) i s’utilitzen tres prompts que presenten instruccions amb diversos nivells de precisió per obtenir les versions posteditades automàticament. Quant a les mètriques lingüístiques, el grau de diversitat lèxica i sintàctica augmenta sistemàticament a la PA en comparació amb la TA en brut: el prompt que presenta el menor grau de restricció desemboca generalment en millores más marcades que el de major grau de restricció. Tanmateix, les mètriques d’avaluació de la qualitat produeixen resultats contraris: els prompts amb menor grau de restricció obtenen puntuacions COMETKiwi inferiors. La comparació qualitativa d’uns fragments de text traduïts automàticament amb fragments posteditats automàticament demostra que la PA pot corregir els errors produïts per la TA, reduir la falta de fluidesa i els calcs, i proposar traduccions més naturals, tot i que també pugui arribar a introduir errors nous.

Paraules clau

traducció automàtica, postedició automàtica, estratègies de prompting, mètriques lingüístiques, diversitat lèxica, equivalència sintàctica

Referències

Alvarez-Vidal, Sergi; do Campo, Maria; Olalla-Soler, Christian; Sánchez-Gijón, Pilar (2025). Using Translation Techniques to Characterize MT Outputs. In: Bouillon, Pierrette; Gerlach, Johanna; Girletti, Sabrina; Volkart, Lise; Rubino, Raphael; Sennrich, Rico; Farinha, Ana C.; Gaido, Marco; Daems, Joke; Kenny, Dorothy; Moniz, Helena; Szoc, Sara (eds.). Proceedings of Machine Translation Summit XX, Volume 1, pp. 619-627. <https://aclanthology.org/volumes/2025.mtsummit-1/>. [Accessed: 20251217].

Baker, Mona (1993). Corpus Linguistics and Translation Studies: Implications and Applications. In: Baker, Mona; Gill, Francis; Tognini-Bonelli, Elena; Sinclair, John (eds.). Text and Technology. Philadelphia: J. Benjamins Pub, pp. 233 250. <https://doi.org/10.1075/z.64.15bak>. [Accessed: 20251217].

Baker, Mona (1995). Corpora in Translation Studies: An Overview and Some Suggestions for Future Research. Target: International Journal of Translation Studies, v. 7 n. 2., pp. 223 243. <https://doi.org/10.1075/target.7.2.03bak>. [Accessed: 20251217].

Bestgen, Yves (2024). Diversité lexicale et longueur du texte en évaluation du langage. In: Dister, Anne; Longrée, Dominique (eds.). Actes des 17es Journées internationales d'Analyse statistique des Données Textuelles, pp. 89-98. <https://perso.uclouvain.be/yves.bestgen/images/JADT24.pdf>. [Accessed: 20251217].

Briva-Iglesias, Vicent (2025). Are AI agents the new machine translation frontier? Challenges and opportunities of single- and multi-agent systems for multilingual digital communication. In: Bouillon, Pierrette; Gerlach, Johanna; Girletti, Sabrina; Volkart, Lise; Rubino, Raphael; Sennrich, Rico; Farinha, Ana C.; Gaido, Marco; Daems, Joke; Kenny, Dorothy; Moniz, Helena; Szoc, Sara (eds.). Proceedings of Machine Translation Summit XX, Volume 1, pp. 365-377. <https://aclanthology.org/volumes/2025.mtsummit-1/>. [Accessed: 20251217].

Castilho, Sheila; Resende, Natalia (2022). Post-Editese in Literary Translations. Information, v. 13 n. 2. <https://doi.org/10.3390/info13020066>. [Accessed: 20251217].

Castilho, Sheila; Resende, Natalia; Mitkov, Ruslan (2019). What Influences the Features of Post-editese? A Preliminary Study. Proceedings of the Human-Informed Translation and Interpreting Technology Workshop (HiT-IT 2019), pp. 19 27. <https://doi.org/10.26615/issn.2683-0078.2019_003>. [Accessed: 20251217].

Chan, Venus; Tang, William Ko-Wai (2024). GPT and Translation: A Systematic Review. 2024 International Symposium on Educational Technology (ISET), pp. 59 63. <https://doi.org/10.1109/ISET61814.2024.00021>. [Accessed: 20251217].

Chen, Pinzhen; Guo, Zhicheng; Haddow, Barry; Heafield, Kenneth (2024). Iterative Translation Refinement with Large Language Models. <https://doi.org/10.48550/arXiv.2306.03856>. [Accessed: 20251217].

Cochrane, Guylaine (1995). Le foisonnement, phénomène complexe. TTR : traduction, terminologie, rédaction, v. 8 n. 2, pp. 175 193. <https://doi.org/10.7202/037222ar>. [Accessed: 20251217].

Cohen, Jacob (2013). Statistical Power Analysis for the Behavioral Sciences. NewYork: Routledge. <https://doi.org/10.4324/9780203771587>. [Accessed: 20251217].

Covington, Michael A.; McFall, Joe D. (2010). Cutting the Gordian Knot: The Moving-Average Type–Token Ratio (MATTR). Journal of Quantitative Linguistics, v. 17 n. 2, pp. 94 100. <https://doi.org/10.1080/09296171003643098>. [Accessed: 20251217].

Čulo, Oliver; Nitzke, Jean (2016). Patterns of Terminological Variation in Post-editing and of Cognate Use in Machine Translation in Contrast to Human Translation. Baltic J. Modern Computing, v. 4 n. 2, pp. 106 114. <https://www.bjmc.lu.lv/fileadmin/user_upload/lu_portal/projekti/bjmc/Contents/4_2_4_Culo.pdf>. [Accessed: 20251217].

Daems, Joke; De Clercq, Orphée; Macken, Lieve (2017). Translationese and Post-editese: How comparable is comparable quality? Linguistica Antverpiensia, New Series: Themes in Translation Studies. v. 16. <https://doi.org/10.52034/lanstts.v16i0.434>. [Accessed: 20251217].

De Clercq, Orphée; De Sutter, Gert; Loock, Rudy; Cappelle, Bert; Plevoets, Koen (2021). Uncovering Machine Translationese Using Corpus Analysis Techniques to Distinguish between Original and Machine-Translated French. Translation Quarterly, n. 101, pp. 21 45. <http://hdl.handle.net/1854/LU-8725139>. [Accessed: 20251217].

Directorate-General for Translation (2025). European Language Industry Survey 2025. <https://elis-survey.org/wp-content/uploads/2025/03/ELIS-2025_Report.pdf>. [Accessed: 20251217].

Do Carmo, Félix; Shterionov, Dimitar; Moorkens, Joss; Wagner, Joachim; Hossari, Murhaf; Paquin, Eric; Schmidtke, Dag; Groves, Declan; Way, Andy (2021). A review of the state-of-the-art in automatic post-editing. Machine Translation, v. 35 n. 2, pp. 101-143. <https://doi.org/10.1007/s10590-020-09252-y>. [Accessed: 20251217].

Dou, Zi-Yi; Neubig, Graham (2021). Word Alignment by Fine-tuning Embeddings on Parallel Corpora. In: Merlo, Paola; Tiedemann, Jorg; Tsarfaty, Reut (eds.). Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pp. 2112 2128. <https://doi.org/10.18653/v1/2021.eacl-main.181>. [Accessed: 20251217].

Du, Shuxiang; Guerberof Arenas, Ana; Toral, Antonio; Gerrits, Kyo; Borillo, Josep Marco (2025). Optimising ChatGPT for creativity in literary translation: A case study from English into Dutch, Chinese, Catalan and Spanish. In: Bouillon, Pierrette; Gerlach, Johanna; Girletti, Sabrina; Volkart, Lise; Rubino, Raphael; Sennrich, Rico; Farinha, Ana C.; Gaido, Marco; Daems, Joke; Kenny, Dorothy; Moniz, Helena; Szoc, Sara (eds.). Proceedings of Machine Translation Summit XX, Volume 1, pp. 578-591. <https://aclanthology.org/volumes/2025.mtsummit-1/>. [Accessed: 20251217].

Farrell, Michael (2018). Machine Translation Markers in Post-Edited Machine Translation Output. Proceedings of the 40th Conference Translating and the Computer, pp. 50-59. <https://apeiron.iulm.it/handle/10808/47325>. [Accessed: 20251217].

Farrell, Michael (2023a). Current evidence of post-editese: differences between post-edited neural machine translation output and human translation revealed through human evaluation. Proceedings of the International Conference on Human-Informed Translation and Interpreting Technology Workshop (HiT-IT 2023), pp. 52-63. <https://doi.org/10.26615/issn.2683-0078.2023_005>. [Accessed: 20251217].

Farrell, Michael (2023b). Preliminary evaluation of ChatGPT as a machine translation engine and as an automatic post-editor of raw machine translation output from other machine translation engines. Proceedings of the International Conference on Human-Informed Translation and Interpreting Technology Workshop (HiT-IT 2023), pp. 108-113. <https://doi.org/10.26615/issn.2683-0078.2023_009>. [Accessed: 20251217].

Fernandes, Patrick; Deutsch, Daniel; Finkelstein, Mara; Riley, Parker; Martins, André; Neubig, Graham; Garg, Ankush; Clark, Jonathan; Freitag, Markus; Firat, Orhan (2023). The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation. In: Koehn, Philipp; Haddow, Barry; Kocmi, Tom; Monz, Christof (eds.). Proceedings of the Eighth Conference on Machine Translation, pp. 1066 1083. <https://doi.org/10.18653/v1/2023.wmt-1.100>. [Accessed: 20251217].

Frawley, William (1984). Prolegomenon to a theory of translation. In: Frawley, William (ed.). Translation: Literary, Linguistic and Philosophical Perspectives. Newark: University of Delaware Press, pp. 159 175.

Gellerstam, Martin (1986). Translationese in Swedish novels translated from English. Translation studies in Scandinavia, v. 1, pp. 88-95.

Guo, Jiaxin; Yang, Hao; Li, Zongyao; Wei, Daimeng; Shang, Hengchao; Chen, Xiaoyu (2024). A Novel Paradigm Boosting Translation Capabilities of Large Language Models. <https://doi.org/10.48550/arXiv.2403.11430>. [Accessed: 20251217].

Hansen, Damien; Esperança-Rodier, Emmanuelle (2022). Human-Adapted MT for Literary Texts: Reality or Fantasy? NeTTT 2022, pp. 178 190. <https://hal.science/hal-04038025>. [Accessed: 20251217].

He, Zhiwei; Liang, Tian; Jiao, Wenxiang; Zhang, Zhuosheng; Yang, Yujiu; Wang, Rui; Tu, Zhaopeng; Shi, Shuming; Wang, Xing (2024). Exploring Human-Like Translation Strategy with Large Language Models. Transactions of the Association for Computational Linguistics, v. 12, pp. 229 246. <https://doi.org/10.1162/tacl_a_00642>. [Accessed: 20251217].

Hedges, Larry V.; Olkin, Ingram (2014). Statistical Methods for Meta-Analysis. Saint-Louis: Elsevier Science.

Hendy, Amr; Abdelrehim, Mohamed; Sharaf, Amr; Raunak, Vikas; Gabr, Mohamed; Matsushita, Hitokazu; Kim, Young Jin; Afify, Mohamed; Awadalla, Hany Hassan (2023). How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation. <https://doi.org/10.48550/arXiv.2302.09210>. [Accessed: 20251217].

Jiao, Wenxiang; Wang, Wenxuan; Huang, Jen-Tse; Wang, Xing; Shi, Shuming; Tu, Zhaopeng (2023). Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine. <https://doi.org/10.48550/arXiv.2301.08745>. [Accessed: 20251217].

Jiménez-Crespo, Miguel A. (2023). “Translationese” (and “post-editese”?) no more: on importing fuzzy conceptual tools from Translation Studies in MT research. In: Nurminen, Mary; Brenner, Judith; Koponen, Maarit; Latomaa, Sirkku; Mikhailov, Mikhail; Schierl, Frederike; Ranasinghe, Tharindu; Vanmassenhove, Eva; Alvarez Vidal, Sergi; Aranberri, Nora; Nunziatini, Mara; Parra Escartín, Carla; Forcada, Mikel; Popovic, Maja; Scarton, Carolina; Moniz, Helena (eds.). Proceedings of the 24th Annual Conference of the European Association for Machine Translation, pp. 261 268 <https://aclanthology.org/2023.eamt-1.25/>. [Accessed: 20251217].

Johansson, Victoria (2008). Lexical diversity and lexical density in speech and writing: a developmental perspective. In: Lund University, Department of Linguistics and Phonetics (eds.). Working Papers, v. 53., pp. 61 79.

Ki, Dayeon; Carpuat, Marine (2024). Guiding Large Language Models to Post-Edit Machine Translation with Error Annotations. In: Duh, Kevin; Gomez, Helena; Bethard, Steven (eds.). Findings of the Association for Computational Linguistics: NAACL 2024, pp. 4253 4273. <https://doi.org/10.18653/v1/2024.findings-naacl.265>. [Accessed: 20251217].

Kocmi, Tom; Avramidis, Eleftherios; Bawden, Rachel; Bojar, Ondřej; Dvorkovich, Anton; Federmann, Christian; Fishel, Mark; Freitag, Markus; Gowda, Thamme; Grundkiewicz, Roman; Haddow, Barry; Karpinska, Marzena; Koehn, Philipp; Marie, Benjamin; Monz, Christof; Murray, Kenton; Nagata, Masaaki; Popel, Martin; Popović, Maja; Shmatova, Mariya; Steingrímsson, Steinthór; Zouhar, Vilém (2024). Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet. In: Haddow, Barry; Kocmi, Tom; Koehn, Philipp; Monz, Christof (eds.). Proceedings of the Ninth Conference on Machine Translation, pp. 1 46. <https://doi.org/10.18653/v1/2024.wmt-1.1>. [Accessed: 20251217].

Kocmi, Tom; Avramidis, Eleftherios; Bawden, Rachel; Bojar, Ondřej; Dvorkovich, Anton; Federmann, Christian; Fishel, Mark; Freitag, Markus; Gowda, Thamme; Grundkiewicz, Roman; Haddow, Barry; Koehn, Philipp; Marie, Benjamin; Monz, Christof; Morishita, Makoto; Murray, Kenton; Nagata, Masaaki; Nakazawa, Toshiaki; Popel, Martin; Popović, Maja; Shmatova, Mariya (2023). Findings of the 2023 Conference on Machine Translation (WMT23): LLMs Are Here but Not Quite There Yet. In: Koehn, Philipp; Haddow, Barry; Kocmi, Tom; Monz, Christof (eds.). Proceedings of the Eighth Conference on Machine Translation, pp. 1 42. <https://doi.org/10.18653/v1/2023.wmt-1.1>. [Accessed: 20251217].

Kocmi, Tom; Zouhar, Vilém; Federmann, Christian; Post, Matt (2024). Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies. In: Ku, Lun-Wei; Martins, Andre; Srikumar, Vivek (eds.). Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1999 2014. <https://doi.org/10.18653/v1/2024.acl-long.110>. [Accessed: 20251217].

Kunilovskaya, Maria; Dutta Chowdhury, Koel; Przybyl, Heike; España-Bonet, Cristina; Genabith, Josef (2024). Mitigating Translationese with GPT-4: Strategies and Performance. In: Scarton, Carolina; Prescott, Charlotte; Bayliss, Chris; Oakley, Chris; Wright, Joanna; Wrigley, Stuart; Song, Xingyi; Gow-Smith, Edward; Bawden, Rachel; Sánchez-Cartagena, Víctor M.; Cadwell, Patrick; Lapshinova-Koltunski, Ekaterina; Cabarrão, Vera; Chatzitheodorou, Konstantinos; Nurminen, Mary; Kanojia, Diptesh; Moniz, Helena. Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1), pp. 411 430. <https://aclanthology.org/2024.eamt-1.35/>. [Accessed: 20251217].

Laviosa, Sara (1998). Core Patterns of Lexical Use in a Comparable Corpus of English Narrative Prose. Meta: Journal des traducteurs = Translator’s Journal. v. 43 n. 4, pp. 557 570. <https://doi.org/10.7202/003425ar>. [Accessed: 20251217].

Laviosa-Braithwaite, Sara (1996). Investigating Simplification in English Comparable Corpus of Newspaper Articles. In: Kinga, Klaudy; Janos, Kohn (eds.). Transferre necesse est: Proceedings of the Second International Conference on Current Trends in Studies of Translation and Interpreting, pp. 531-540. [Accessed: 20251217].

Li, Yafu; Zhang, Ronghao; Wang, Zhilin; Zhang, Huajian; Cui, Leyang; Yin, Yongjing; Xiao, Tong; Zhang, Yue (2025). Lost in Literalism: How Supervised Training Shapes Translationese in LLMs. <https://doi.org/10.48550/arXiv.2503.04369>. [Accessed: 20251217].

Loock, Rudy (2018). Traduction automatique et usage linguistique : une analyse de traductions anglais-français réunies en corpus. Meta: Journal des traducteurs = Translator’s Journal v. 63 n. 3, pp. 785-805. <https://doi.org/10.7202/1060173ar>. [Accessed: 20251217].

Macken, Lieve (2024). Machine translation meets large language models: evaluating ChatGPT’s ability to automatically post-edit literary texts. In: Vanroy, Bram; Lefer, Marie-Aude; Macken, Lieve; Ruffo, Paola (eds.). Proceedings of the First Workshop on Creative-text Translation and Technology, pp. 71 87. <https://aclanthology.org/2024.ctt-1.7/>. [Accessed: 20251217].

Marques, Francisco Paulo Jamil; Mont’Alverne, Camila (2021). What are newspaper editorials interested in? Understanding the idea of criteria of editorial-worthiness. Journalism. v. 22 n. 7., pp. 1812 1830. <https://doi.org/10.1177/1464884919828503>. [Accessed: 20251217].

Martikainen, Hanna; Kübler, Natalie (2016). Ergonomie cognitive de la post-édition de traduction automatique : enjeux pour la qualité des traductions. ILCEA. Revue de l’Institut des langues et cultures d’Europe, Amérique, Afrique, Asie et Australie, n. 27. <https://doi.org/10.4000/ilcea.3863>. [Accessed: 20251217].

McNamara, Danielle S.; Graesser, Arthur C.; McCarthy, Philip M.; Cai, Zhiqiang (2014). Automated Evaluation of Text and Discourse with Coh-Metrix. New York: Cambrigde University Press. <https://doi.org/10.1017/CBO9780511894664>. [Accessed: 20251217].

Moslem, Yasmin; Haque, Rejwanul; Kelleher, John D.; Way, Andy (2023). Adaptive Machine Translation with Large Language Models. arXiv:2301.13294v3. <https://doi.org/10.48550/arXiv.2301.13294>. [Accessed: 20251217].

Niu, Jiang; Jiang, Yue (2024). Does simplification hold true for machine translations? A corpus-based analysis of lexical diversity in text varieties across genres. Humanities and Social Sciences Communications. v. 11 n. 1. <https://doi.org/10.1057/s41599-024-02986-7>. [Accessed: 20251217].

OpenAI, Achiam, Josh; Adler, Steven; Agarwal, Sandhini; … Zoph, Barret (2024). GPT-4 Technical Report. arXiv.2303.08774v6. <https://doi.org/10.48550/arXiv.2303.08774>. [Accessed: 20251217].

Peng, Keqin; Ding, Liang; Zhong, Qihuang; Shen, Li; Liu, Xuebo; Zhang, Min; Ouyang, Yuanxin; Tao, Dacheng (2023). Towards Making the Most of ChatGPT for Machine Translation. <https://doi.org/10.48550/arXiv.2303.13780>. [Accessed: 20251217].

Poibeau, Thierry (2022). On “Human Parity” and “Super Human Performance” in Machine Translation Evaluation. In: Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Odijk, Jan; Piperidis, Stelios (eds.). Proceedings of the Thirteenth Language Resources and Evaluation Conference, pp. 6018 6023. <https://aclanthology.org/2022.lrec-1.647/>. [Accessed: 20251217].

Puppel, Melissa; Borg, Claudine (2024). Evaluating ChatGPT’s Performance in Creative Text Translation for Communication: A Case Study from English into German. Media and Intercultural Communication: A Multidisciplinary Journal, v. 3, n. 1 (March). 1<https://doi.org/10.22034/mic.2024.480506.1023>. [Accessed: 20251217].

Qi, Peng; Zhang, Yuhao; Zhang, Yuhui; Bolton, Jason; Manning, Christopher D. (2020). Stanza: A Python Natural Language Processing Toolkit for Many Human Languages. In: Celikyilmaz, Asli; Wen, Tsung-Hsien (eds.). Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 101 108. <https://doi.org/10.18653/v1/2020.acl-demos.14>. [Accessed: 20251217].

Raunak, Vikas; Menezes, Arul; Post, Matt; Hassan, Hany (2023). Do GPTs Produce Less Literal Translations? In: Rogers, Anna; Boyd-Graber, Jordan; Okazaki, Naoaki (eds.). Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 1041 1050. <https://doi.org/10.18653/v1/2023.acl-short.90>. [Accessed: 20251217].

Raunak, Vikas; Sharaf, Amr; Wang, Yiren; Awadallah, Hany Hassan; Menezes, Arul (2023). Leveraging GPT-4 for Automatic Translation Post-Editing. In: Bouamor, Houda; Pino, Juan; Bali, Kalika (eds.). Findings of the Association for Computational Linguistics: EMNLP 2023. <10.18653/v1/2023.findings-emnlp.804>. [Accessed: 20251217].

Rei, R.; Stewart, C.; Farinha, A. C.; Lavie, A. (2020). COMET: A Neural Framework for MT Evaluation. In: Webber, Bonnie; Cohn, Trevor; He, Yulan; Liu, Yang (eds.). Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 2685 2702. <https://doi.org/10.18653/v1/2020.emnlp-main.213>. [Accessed: 20251217].

Rei, Ricardo; C. de Souza, José G.; Alves, Duarte; Zerva, Chrysoula; Farinha, Ana C.; Glushkova, Taisiya; Lavie, Alon; Coheur, Luisa; Martins, André F. T. (2022a). COMET-22: Unbabel-IST 2022 Submission for the Metrics Shared Task. In: Koehn, Philipp; Barrault, Loïc; Bojar, Ondřej; Bougares, Fethi; Chatterjee, Rajen; et al (eds.). Proceedings of the Seventh Conference on Machine Translation (WMT), pp. 578 585. <https://aclanthology.org/2022.wmt-1.52/>. [Accessed: 20251217].

Rei, Ricardo; Treviso, Marcos; Guerreiro, Nuno M.; Zerva, Chrysoula; Farinha, Ana C.; Maroti, Christine; C. de Souza, José G.; Glushkova, Taisiya; Alves, Duarte; Coheur, Luisa; Lavie, Alon; Martins, André F. T. (2022b). CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task. In: Koehn, Philipp; Barrault, Loïc; Bojar, Ondřej; Bougares, Fethi; Chatterjee; et al. (eds.). Proceedings of the Seventh Conference on Machine Translation (WMT), pp. 634 645. <https://aclanthology.org/2022.wmt-1.60/>. [Accessed: 20251217].

Schumacher, Perrine (2025). Exploration des répercussions de la TA neuronale sur la langue cible après post-édition en contexte d’apprentissage : qu’en est-il du post-editese ? Langages. v. 237 n. 1., pp. 109 130. <https://doi.org/10.3917/lang.237.0109>. [Accessed: 20251217].

Toral, Antonio (2019). Post-editese: an Exacerbated Translationese. In: Forcada, Mikel; Way, Andy; Haddow, Barry; Sennrich, Rico (eds.). Proceedings of Machine Translation Summit XVII: Research Track, pp. 273 281. <https://aclanthology.org/W19-6627/>. [Accessed: 20251217]..

Vanmassenhove, Eva; Shterionov, Dimitar; Gwilliam, Matthew (2021). Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation. In: Merlo, Paola; Tiedemann, Jorg; Tsarfaty, Reut (eds.). Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pp. 2203 2213. <https://doi.org/10.18653/v1/2021.eacl-main.188>. [Accessed: 20251217].

Vanmassenhove, Eva; Shterionov, Dimitar; Way, Andy (2019). Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation. In: Forcada, Mikel; Way, Andy; Haddow, Barry; Sennrich, Rico (eds.). Proceedings of Machine Translation Summit XVII: Research Track, pp. 222 232. <https://aclanthology.org/W19-6622/>. [Accessed: 20251217].

Vanroy, Bram; De Clercq, Orphée; Tezcan, Arda; Daems, Joke; Macken, Lieve (2021). Metrics of syntactic equivalence to assess translation difficulty. In Explorations in empirical translation process research. v. 3, pp. 259 294. <https://doi.org/10.1007/978-3-030-69777-8_10>. [Accessed: 20251217].

Vanroy, Bram; Tezcan, Arda; Macken, Lieve (2019). Predicting syntactic equivalence between source and target sentences. Computational Linguistics in the Netherlands Journal. v. 9, pp. 101 116. <https://clinjournal.org/clinj/article/view/95>. [Accessed: 20251217].

Vilar, David; Freitag, Markus; Cherry, Colin; Luo, Jiaming; Ratnakar, Viresh; Foster, George (2023). Prompting PaLM for Translation: Assessing Strategies and Performance. arXiv:2211.09102v3. <https://doi.org/10.48550/arXiv.2211.09102>. [Accessed: 20251217].

Volkart, Lise; Bouillon, Pierrette (2022). Studying Post-Editese in a Professional Context: A Pilot Study. In: Moniz, Helena; Macken, Lieve; Rufener, Andrew; Barrault, Loïc; Costa-jussà, Marta R.; Declercq, Christophe; Koponen, Maarit; Kemp, Ellie; Pilos, Spyridon; Forcada, Mikel L.; Scarton, Carolina; Van den Bogaert, Joachim; Daems, Joke; Tezcan, Arda; Vanroy, Bram; Fonteyne, Margot (eds.). Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pp. 71 79. <https://aclanthology.org/2022.eamt-1.10/>. [Accessed: 20251217].

Volkart, Lise; Bouillon, Pierrette (2023). Are post-editese features really universal? In: Orăsan, Constantin; Mitkov, Ruslan; Corpas Pastor, Gloria; Monti, Johanna (eds.). Proceedings of the International Conference on Human-informed Translation and Interpreting Technology 2023, pp. 294 304. <https://doi.org/10.26615/issn.2683-0078.2023_025>. [Accessed: 20251217].

Volkart, Lise; Bouillon, Pierrette (2024). Post-editors as Gatekeepers of Lexical and Syntactic Diversity: Comparative Analysis of Human Translation and Post-editing in Professional Settings. In: Scarton, Carolina; Prescott, Charlotte; Bayliss, Chris; Oakley, Chris; Wright, Joanna; Wrigley, Stuart; Song, Xingyi; Gow-Smith, Edward; Bawden, Rachel; Sánchez-Cartagena, Víctor M.; Cadwell, Patrick; Lapshinova-Koltunski, Ekaterina; Cabarrão, Vera; Chatzitheodorou, Konstantinos; Nurminen, Mary; Kanojia, Diptesh; Moniz, Helena. Proceedings of the 25th Annual Conference of the European Association for Machine Translation, pp. 387 395. <https://aclanthology.org/2024.eamt-1.33/>. [Accessed: 20251217].

Wang, Longyue; Lyu, Chenyang; Ji, Tianbo; Zhang, Zhirui; Yu, Dian; Shi, Shuming; Tu, Zhaopeng (2023). Document-Level Machine Translation with Large Language Models. arXiv:2304.02210v2. <https://doi.org/10.48550/arXiv.2304.02210>. [Accessed: 20251217].

Wei, Jason; Wang, Xuezhi; Schuurmans, Dale; Bosma, Maarten; Ichter, Brian; Xia, Fei; Chi, Ed; Le, Quoc; Zhou, Denny (2022). Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. <https://doi.org/10.48550/arXiv.2201.11903>. ArXiv:2201.11903v6. [Accessed: 20251217].

Xu, Haoran; Kim, Young Jin; Sharaf, Amr; Awadalla, Hany Hassan (2024). A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models. arXiv:2308.01391v2. <https://doi.org/10.48550/arXiv.2309.11674>. [Accessed: 20251217].

Yamada, Masaru (2024). Optimizing Machine Translation through Prompt Engineering: An Investigation into ChatGPT’s Customizability. arXiv:2308.01391v2. <https://doi.org/10.48550/arXiv.2308.01391>. [Accessed: 20251217].

Zhang, Biao; Haddow, Barry; Birch, Alexandra (2023). Prompting Large Language Model for Machine Translation: A Case Study. arXiv:2301.07069v2. <https://doi.org/10.48550/arXiv.2301.07069>. [Accessed: 20251217].

Zhu, Wenhao; Liu, Hongyi; Dong, Qingxui; Xu, Jingjing; Huang, Shujian; Kong, Lingpeng; Chen, Jiajun; Li, Lei (2024). Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis. In: Duh, Kevin; Gomez, Helena; Bethard, Steven (eds.). Findings of the Association for Computational Linguistics: NAACL 2024, pp. 2765 2781. <https://doi.org/10.18653/v1/2024.findings-naacl.176>. [Accessed: 20251217].

Biografia de l'autor/a

Valentin Scourneau, Polytechnic University of Hauts-de-France

Joint PhD Student at the University of Mons (English Unit: Literature, Language, Interpretation and Translation) and Polytechnic University of Hauts-de-France (LARSH department)

Publicades

22-12-2025

Com citar

(1)
Scourneau, V. Impacte De La Postedició automàtica I De Les estratègies De Prompting En Les característiques lingüístiques De Les Traduccions Editorials De l’anglès Al francès. tradumatica 2025, 65-100.

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