Explanation

Correct Answer: B (Hierarchical Chunking)

Why Hierarchical Chunking is the best solution:

1. Preserves semantic context across related paragraphs: Hierarchical chunking creates parent-child relationships where parent chunks contain broader context (1,000 tokens) while child chunks contain more granular content (200 tokens). This structure maintains the relationship between different levels of content.

2. Maintains context at scale: The parent chunks (1,000 tokens) can capture the broader semantic meaning across multiple paragraphs, while the child chunks (200 tokens) allow for more precise retrieval of specific information.

3. Overlap strategy: The 50-token overlap between chunks helps maintain continuity and prevents loss of context at chunk boundaries.

Why other options are not optimal:

A (Fixed-size chunking):

• Uses arbitrary fixed boundaries (300 tokens) that may cut through meaningful semantic units
• 10% overlap is minimal and may not adequately preserve context across related paragraphs
• Doesn't account for the hierarchical structure of documents

C (Semantic chunking):

• While semantic chunking groups content by meaning, the specific parameters (buffer size of 1, 85% threshold) may not be optimal for preserving context across the entire corpus
• Doesn't explicitly create hierarchical relationships that can help with context preservation at different scales

D (No chunking, manual splitting):

• Manual splitting is not scalable for large corpora
• Loses the ability to automatically maintain semantic relationships
• Post-processing reranking is reactive rather than proactive in preserving context

Key Takeaway: Hierarchical chunking is particularly effective for knowledge bases because it maintains both granular details (in child chunks) and broader context (in parent chunks), which is essential for preserving semantic relationships across related paragraphs at scale.