Semantic Chunking and the Entropy of Natural Language
The model connects natural language structure to its uncertainty using an entropy rate derived from hierarchical semantic organization. It proposes that text can be self-similarly segmented into coherent chunks, and this process reveals that language redundancy increases systematically with semantic complexity, captured by a single parameter representing working memory capacity.