செயற்கை நுண்ணறிவு (AI) மற்றும் Prompt Engineering வழி தமிழ் இலக்கிய ஆய்வு: புதிய ஆராய்ச்சி அணுகுமுறைகள்

Tamil Literary Research through Artificial Intelligence (AI) and Prompt Engineering: New Research Approaches

Authors

  • Dr. R.Kannan Assistant Professor, Department of Tamil and other Languages, RVS College of Arts & Science, Sulur, Coimbatore - 641 402. Author
  • Dr M.Ramachandran Associate Professor In Tamil, Nandha Arts And Science College (Autonomous), Erode. Author

DOI:

https://doi.org/10.63300/tm12022026.43

Keywords:

Artificial Intelligence, Prompt Engineering, Tamil Literature, Large Language Model, Computational Tamilology

Abstract

Tamil literary research has traditionally been rooted in textual analysis, comparative study, and historical approaches. However, recent advancements in Large Language Models (LLMs) and Prompt Engineering techniques have introduced new tools and methodologies to the field of Tamil literary studies. This paper explores how artificial intelligence and Prompt Engineering techniques can be applied to Tamil literary research. Specifically, focusing on language models, datasets, and evaluation metrics developed for Tamil within the context of low-resource languages, this paper describes how these can be utilized for tasks such as text analysis, sentiment analysis, summarization, translation, and question-answering systems. Additionally, the paper highlights the challenges, ethical concerns, and the necessity of human expertise when adopting these technologies.

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Author Biographies

  • Dr. R.Kannan, Assistant Professor, Department of Tamil and other Languages, RVS College of Arts & Science, Sulur, Coimbatore - 641 402.

    முனைவர் அர.கண்ணன், உதவிப் பேராசிரியர்., தமிழ் மற்றும் பிற மொழிகள் துறை, ஆர்.வி.எஸ் கலை மற்றும் அறிவியல் கல்லூரி, சூலூர்,கோயம்புத்தூர்.

    Dr. R.Kannan*, Assistant Professor, Department of Tamil and other Languages, RVS College of Arts & Science, Sulur, Coimbatore - 641 402.

    *Corresponding Author Email: vaanavilkannan@gmail.com.

  • Dr M.Ramachandran, Associate Professor In Tamil, Nandha Arts And Science College (Autonomous), Erode.

    முனைவர் மா. இராமச்சந்திரன், இணைப் பேராசிரியர், தமிழ்த் துறை, நந்தா கலை மற்றும் அறிவியல் கல்லூரி (தன்னாட்சி)-ஈரோடு.

    Dr M.Ramachandran, Associate Professor In Tamil, Nandha Arts And Science College (Autonomous), Erode.

    Email: rampiththan@gmail.com

    Orcid id: https://orcid.org/0009-0000-3815-4580

References

[1.] Balachandran, A. (2023). Tamil-LLaMA: A new Tamil language model based on Llama 2. arXiv preprint arXiv:2311.05845.

[2.] Brindha, S. (2024). நற்றிணை – மருதத்திணையில் நகை மெய்ப்பாடு. International Journal of Creative Research Thoughts (IJCRT), 12(11), a611–a618.

[3.] Chakravarthi, B. R., Priyadharshini, R., Muralidaran, V., Jose, N., Suryawanshi, S., Sherly, E., & McCrae, J. P. (2022). DravidianCodeMix: Sentiment analysis and offensive language identification dataset for Dravidian languages in code-mixed text. Language Resources and Evaluation, 56(3), 765–806.

[4.] Doddapaneni, S., Aralikatte, R., Ramesh, G., Goyal, S., Khapra, M. M., Kunchukuttan, A., & Kumar, P. (2023). Towards leaving no Indic language behind: Building monolingual corpora, benchmark and models for Indic languages. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, 1, 12402–12426.

[5.] Minaee, S., Mikolov, T., Nikzad, N., Chenaghlu, M., Socher, R., Amatriain, X., & Gao, J. (2024). Large language models: A survey. arXiv preprint arXiv:2402.06196.

[6.] Premjith, B., Bharathi, B., Chakravarthi, B. R., et al. (2023). Findings of the shared task on multimodal sentiment analysis and emotion analysis in Tamil and Malayalam. Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages.

[7.] Raja, R. (2022). சங்க கால வாழ்வியல் விழுமியங்கள்: புறநானூற்றில் அரசியல் அறங்கள். International Journal of Creative Research Thoughts (IJCRT), 10(3), 849–855.

[8.] Ramesh, T. K., & Thamilarasi, P. (2025). Sense of self & related behaviour: A behavioral psychology perspective in Purananooru. International Journal of Creative Research Thoughts (IJCRT), 13(8), g173–g179.

[9.] Ranathunga, S., Lee, E.-S. A., Prifti Skenduli, M., Shekhar, R., Alam, M., & Kaur, R. (2023). Neural machine translation for low-resource languages: A survey. ACM Computing Surveys, 55(11), 1–37.

[10.] Sahoo, P., Singh, A. K., Saha, S., Jain, V., Mondal, S., & Chadha, A. (2024). A systematic survey of prompt engineering in large language models: Techniques and applications. arXiv preprint arXiv:2402.07927.

[11.] Sopa, R., & Murugeswari, N. (2023). பதினெண்கீழ்க்கணக்கு நூல்களில் கற்பு. International Journal of Creative Research Thoughts (IJCRT), 11(3), 745–750.

[12.] Varsha, J., et al. (2025). From phonemes to meaning: Evaluating large language models on Tamil. arXiv preprint arXiv:2511.12387.

[13.] Vatsal, S., & Dubey, H. (2024). A survey of prompt engineering methods in large language models for different NLP tasks. arXiv preprint arXiv:2407.12994.

[14.] Veerakannan, S. (2025). Artificial intelligence technology: A boon in writing Tamil essays. Tamilmanam International Research Journal of Tamil Studies, 1(04), 221–228. https://doi.org/10.63300/dn796x92

[15.] Veerakannan, S., & Vijayakumar, M. (2025). Artificial intelligence for Tamil literature: An overview. Tamilmanam International Research Journal of Tamil Studies, 1(07), 363–370. https://doi.org/10.63300/eanb2p66

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Published

07/20/2026

How to Cite

செயற்கை நுண்ணறிவு (AI) மற்றும் Prompt Engineering வழி தமிழ் இலக்கிய ஆய்வு: புதிய ஆராய்ச்சி அணுகுமுறைகள்: Tamil Literary Research through Artificial Intelligence (AI) and Prompt Engineering: New Research Approaches. (2026). Tamilmanam International Research Journal of Tamil Studies, 12(02), 586-600. https://doi.org/10.63300/tm12022026.43

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