Prompt-Based Anaphora Resolution in Large Language Models

Authors

  • Mridusmita Das Central Institute of Technology Kokrajhar
  • Apurbalal Senapati Central Institute of Technology Kokrajhar
  • Apurbalal Senapati Central Institute of Technology Kokrajhar

DOI:

https://doi.org/10.13053/cys-29-3-5917

Keywords:

Anaphora resolution, prompt engineering, large language models, assamese language, low-resource NLP, peer-to-peer network

Abstract

With the advancement of Large Language Models (LLMs), the scope of research in the Natural Language Processing (NLP) domain has significantly shifted. The LLM has context-based advanced language understanding that is suitable for various types of discourse analysis. Creating suitable prompts can effectively guide the model’s responses toward the desired outcome. Anaphora resolution is a complex problem that is highly context-dependent. This paper attempted to explore a prompt-based LLM technique for the resolution of anaphora. Our experiment used a \textbf{text-based question} prompt within the OpenAI LLM framework. The experiment is conducted in the Assamese language, initially using a rule-based system. The results are then compared with those obtained from a prompt-based approach. The main contribution of this paper is the exploration of prompt engineering techniques for anaphora resolution. The results indicate that the prompt-based approach is significantly superior to the rule-based approach.

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Published

2025-09-28

Issue

Vol. 29 No. 3 (2025): Vol 29 No 3 (2025)

Section

Articles of the Thematic Section

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