Shallow Parser

Shallow parsing, a crucial task in natural language processing (NLP), aims to analyze sentence structure at a basic level, identifying parts of speech and phrase chunks. Current research emphasizes developing robust and scalable shallow parsers, often leveraging transformer-based architectures and incorporating linguistic knowledge to improve accuracy, particularly for low-resource languages. This work is vital for numerous NLP applications, including machine translation, sentiment analysis, and information extraction, and contributes to a deeper understanding of linguistic structure through data-driven theoretical modeling.