Chunking for Multilingual Content — Language-Aware Splitting

I will implement language-aware chunking for your multilingual document corpus — detecting document language, applying language-specific tokenisation and sentence boundary detection, handling mixed-language documents that switch languages mid-section, and configuring language-appropriate chunk sizes based on the average token-to-character ratios of each language. Multilingual chunking with language-agnostic character-count splitting produces inconsistent chunk sizes across languages — Chinese text at 512 characters contains far more semantic content than English text at 512 characters because Chinese characters represent morphemes where English characters represent phonemes; language-aware token-based splitting produces semantically equivalent chunks across languages.

The implementation covers language detection per document and section, language-specific tokeniser integration, sentence boundary detection for each supported language, mixed-language document handling, token-based chunk size calibration per language, and retrieval quality comparison across languages.