SnowPro Specialty: Gen AI Question 135
Single answerSPLIT_TEXT_RECURSIVE_CHARACTERA team is building a retrieval-augmented generation (RAG) pipeline in Snowflake over long product manuals stored as raw text. They want to create chunks that preserve paragraph and sentence boundaries when possible, but still guarantee that very long sections are split into smaller pieces for embedding. The engineer is considering SPLIT_TEXT_RECURSIVE_CHARACTER for preprocessing. Which approach best fits this requirement?
- A
Use SPLIT_TEXT_RECURSIVE_CHARACTER with an ordered list of separators from larger boundaries to smaller ones so the function tries paragraphs first, then sentences, and only then falls back to finer splits.
- B
Use SPLIT_TEXT_RECURSIVE_CHARACTER with a single separator only, because recursive splitting works only when one delimiter is provided and additional separators are ignored.
- C
Avoid SPLIT_TEXT_RECURSIVE_CHARACTER and instead use a fixed-width character split exclusively, because recursive character splitting cannot enforce maximum chunk sizes.
- D
Use SPLIT_TEXT_RECURSIVE_CHARACTER after generating embeddings, so the vectorization step can determine the best semantic boundaries before the text is chunked.
Show answer and explanation
Correct answer: A
Explanation
The best answer is to use SPLIT_TEXT_RECURSIVE_CHARACTER with separators ordered from coarse to fine boundaries. This aligns with common chunking best practices for RAG systems: preserve higher-level semantic structure where possible, but ensure oversized text is still broken into manageable chunks for embedding and retrieval. In Snowflake Cortex text processing workflows, recursive splitting is appropriate when simple fixed-size chunking would damage context by cutting through paragraphs or sentences unnecessarily. A typical implementation strategy is to attempt larger separators first, then progressively smaller ones until the chunking target can be met. This produces chunks that are usually more coherent for downstream embedding and retrieval tasks.
- A. Correct.
Correct. SPLIT_TEXT_RECURSIVE_CHARACTER is designed for hierarchical text splitting. In a RAG workflow, the practical pattern is to provide separators in priority order, such as paragraph breaks before sentence-level punctuation and then smaller fallbacks. This helps preserve natural structure while still breaking oversized text into smaller chunks when higher-level boundaries are insufficient.
- B. Incorrect.
Incorrect. This reflects a common misunderstanding. Recursive character splitting is useful specifically because it can work through multiple separators in sequence. Limiting it to a single separator removes much of the benefit and does not match the intended hierarchical behavior.
- C. Incorrect.
Incorrect. Fixed-width splitting is sometimes used, but it does not best satisfy the stated requirement to preserve paragraph and sentence boundaries when possible. Recursive splitting is intended to retain more meaningful text structure while still producing chunks that fit size constraints.
- D. Incorrect.
Incorrect. Chunking is generally performed before embedding generation, not after. Embeddings are created from the resulting chunks. Waiting until after vectorization would not help define chunk boundaries for the original source text and would be backwards for a standard RAG preprocessing pipeline.