Semantics in Natural Language Processing: Significance and Applications – A Review

In recent years, the field of Artificial Intelligence (AI), particularly Natural Language Processing (NLP), has witnessed substantial growth, with semantics emerging as a crucial component in enhancing both machine understanding and human language generation. This review explores the pivotal role of semantics in NLP, highlighting its significance, associated challenges, core methodologies, and wide-ranging applications. By examining the intricate relationship between language and meaning, the paper prokvides a comprehensive overview of how semantic understanding drives the development and implementation of NLP technologies. A key focus is placed on linguistic feature extraction, which serves as the foundation for effective semantic analysis. Accurate semantic processing is shown to be essential for improving tasks such as Machine Translation (MT). Ultimately, this review underscores the impact of semantics in advancing NLP capabilities and shaping the future of human-machine interaction through semantic-driven NLP techniques.