Linguistic Structure

Linguistic structure research aims to understand how human language is organized, focusing on the systematic combination of meaningful units to create complex expressions. Current research employs diverse computational methods, including statistical modeling (e.g., minimizing excess entropy), distributional semantics, and model-theoretic approaches, often applied to large corpora and leveraging neural language models (like Transformers) to analyze linguistic phenomena across various levels (phonology, morphology, syntax, semantics). These investigations are crucial for advancing natural language processing (NLP) applications and providing deeper insights into the cognitive mechanisms underlying human language comprehension and production.