GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #85
Which of the following are key considerations when identifying source documents for a RAG application? (Choose two.)
The correct answer is A. Information density D. Document relevance to the task. When selecting source documents for RAG, the content quality and relevance to the task matter far more than physical document properties like size or format.
Question
Which of the following are key considerations when identifying source documents for a RAG application? (Choose two.)
Options
- AInformation density
- BDocument size
- CDocument format
- DDocument relevance to the task
How the community answered
(39 responses)- A87% (34)
- B8% (3)
- C5% (2)
Why each option
When selecting source documents for RAG, the content quality and relevance to the task matter far more than physical document properties like size or format.
Information density ensures that retrieved chunks contain meaningful, actionable content rather than noise or filler text, which directly improves the signal-to-noise ratio of context passed to the LLM.
Document size is a preprocessing and chunking concern, not a source selection criterion - large documents can be chunked and small documents can still be high quality.
Document format affects the parsing and ingestion pipeline but does not determine whether a source is appropriate for the RAG application's knowledge base.
Document relevance to the task is the foundational criterion for RAG source selection - including off-topic documents pollutes the vector index and causes the retriever to surface irrelevant context, degrading response quality.
Concept tested: RAG source document selection criteria
Source: https://docs.databricks.com/en/generative-ai/retrieval-augmented-generation.html
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