Title: From Rules to Reasoning: Impact of NLP on Knowledge-Based Systems
Authors: Sahar E. Altallaa and Samy S. Abu-Naser
Volume: 9
Issue: 8
Pages: 148-153
Publication Date: 2025/08/28//
Abstract:
Natural Language Processing (NLP) plays a pivotal role in the evolution of modern Knowledge-Based Systems (KBS) by enabling computers to process, understand, and extract valuable insights from vast quantities of unstructured human language data. This paper explores the intersection of NLP and KBS, detailing how NLP techniques facilitate the construction and enhancement of knowledge bases through semantic information and structured representations. It discusses the historical development of NLP, from rule-based to advanced machine learning approaches, including deep learning models like Transformers. The paper outlines the methodologies employed for knowledge extraction, such as semantic lexicon construction, ontology development, and information integration. Furthermore, it addresses the significant benefits offered by NLP in diverse applications, particularly in healthcare and information management, while also examining the persistent challenges related to data quality, linguistic ambiguity, generalizability, and ethical considerations. This work aims to provide a comprehensive overview of how NLP contributes to building more intelligent and efficient KBS, and to identify areas for future research and development.