نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه زبان‌ و ادبیات، دانشگاه علوم اسلامی شهید محلاتی، قم، ایران،

2 گروه زبان و ادبیات انگلیسی، دانشکده علوم انسانی، دانشگاه یاسوج

چکیده

مدل‌های تحلیل داده­های زبانی مبتنی بر هوش مصنوعی، به دلیل بسط نظری و عملی، در سال­های اخیر، توجه محققان را به خود جلب کرده است. در این میان، ترجمه ماشینی و ترجمه مبتنی بر هوش مصنوعی، نقطه محوری این پیشرفت‌ها بوده است و درعین‌حال سؤالات زیادی در زمینه کارایی و صحت عملکرد آن‌ها مطرح شده است. تحقیق حاضر تلاشی است تا با کاربست یک قالب ارزیاب ترجمه از زبانشناسی نقش­گرای نظام­مند، صحت انتقال فراکارکردهای اندیشگانی متون قرآن از عربی به انگلیسی را در چت جی‌پی‌تی (نسخه 4) مورد بررسی قرار دهد. بدین منظور صحت انتقال شش دسته فراکارکرد اندیشگانی رفتاری، ذهنی، کلامی، مادی، رابطه­ای و وجودی در 200 آیه منتخب از سوره­های قرآن بر اساس گروه فعلی مرتبط، مشارکان فرایند و شرایط تحقق هر فرایند، مورد بررسی قرار گرفت. نتایج حاصل از تحقیق نشان داد که چت­ جی­پی­تی در بیشتر موارد بررسی‌شده قادر به انتقال فرایندهای مادی، رفتاری و وجودی بوده است درحالی‌که در انتقال فرایندهای ذهنی و رابطه­ای موفق نبوده است. به نظر می­رسد که موفقیت در بخش ابتدایی به دلیل توانایی هوش مصنوعی در تشخیص تمایزات و مشخصات فرایندها نیست بلکه به دلیل تحدید گروه فعلی­ و عینی­تر بودن واحدهای معنایی، مشارکان و شرایط تحقق فرایندهای مادی، رفتاری و وجودی است. ازآنجایی‌که مشخصات ادات کلام در زبانشناسی نقش­گرای برای هر فرایند تبیین و تعریف شده است، می‌توان این مشخصات را در قالب افزونه­های نحوی-معنوی در الگوهای ترجمه ماشینی و هوش مصنوعی به واحدهای لغوی-دستوری الصاق کرد و خطای ماشین در عدم شناخت و انتقال این فراکارکردهای اندیشگانی را کاهش داد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Investigating the Accuracy of GPT’s Translation in Transferring Syntax-Semantic Interface: A Case Study of Ideational Meta-Functions in English Translation of Quran

نویسندگان [English]

  • Sajjad Farokhipour 1
  • Davoud Padiz 2
  • Bamshad Hekmatshoartabari 2

1 Department of Language and Literature, Shahid Mahallati University of Islamic Sceinces, Qom, Iran.

2 Department of English Language and Literature, Fculty of Hunamities, Yasuj University

چکیده [English]

AI-based models of analyzing linguistic data have attracted researchers due to the theoretical and practical spread of these models in recent years. Among them, machine translation and AI-based translation have been a focal point in this development However, many questions regarding their efficiency and accuracy are raised at the same time. The current research is an attempt to employ an evaluative framework from systemic functional linguistics and investigate the accuracy of the transfer of ideational meta-function in the English translation of Quranic verses by GPT-4o. To this aim, 200 verses of the holy Quran were selected purposively and the transfer of six categories of the aforesaid meta-functions including material, verbal, existential, mental, behavioral, and existential were explored based on verb category, participants, and conditions of each process. Results revealed that GPT has been able to transfer material, behavioral, and existential processes while failing to transfer mental and relational processes. It seems that GPT’s success in the first section cannot be attributed to AI’s ability to distinguish the qualities and conditions of the processes but to the limitedness of verbal category and objectivity of their semantic components, participant types, and conditions. Since the characteristics of each part of speech for each process are determined and defined in systemic functional linguistics, they can be attached to the machine translation models in the form of syntactic-semantic tags added to each lexical-grammatical unit to increase the accuracy of translation.

کلیدواژه‌ها [English]

  • Machine Translation
  • Quran Language
  • Functional Linguistics
  • Meta-Function
  • Artificial Intelligence
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