Principle:Hpcaitech ColossalAI Text Splitting Chunking
| Knowledge Sources | |
|---|---|
| Domains | RAG, NLP |
| Last Updated | 2026-02-09 00:00 GMT |
Overview
A text segmentation pattern that splits documents into small, overlapping chunks suitable for embedding and retrieval, with language-specific boundary detection.
Description
Text splitting divides large documents into chunks that fit within embedding model context windows while preserving semantic coherence. ColossalQA provides a Chinese-specific splitter that handles CJK punctuation boundaries in addition to standard recursive character splitting.
Usage
Use after document loading and before embedding to create retrieval-ready chunks.
Theoretical Basis
Chunking parameters:
- chunk_size: Maximum characters per chunk (50 for Chinese, 100 for universal)
- chunk_overlap: Overlap between adjacent chunks for context continuity
- separators: Ordered list of boundary characters (paragraphs -> sentences -> characters)
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