Vector Search: Chunking a Manual
Question Variations
- "Why can large chunks reduce retrieval precision?"
- "How should tables and code blocks be chunked?"
- "How would you chunk a technical manual containing headings, tables, and code?"
Why This Is Asked
This tests whether a candidate understands that chunking determines what evidence retrieval can return. Interviewers assess semantic boundaries, metadata preservation, and an empirical method for balancing context completeness against retrieval precision.
Key Concepts
- Semantic boundaries: Preserve sections and parent context rather than splitting arbitrary token counts.
- Chunk size: Balance retrieval precision against sufficient answer context.
- Metadata: Retain document hierarchy, version, and permissions.
- Evaluation: Test evidence recall and answer quality on representative queries.
Question Variations
- “Why can large chunks reduce retrieval precision?”
- “How should tables and code blocks be chunked?”
- “How would you chunk a technical manual containing headings, tables, and code?”