Definition
Completeness refers to the degree to which an LLM-generated response addresses all components of a user's query using the entirety of the relevant retrieved context. In RAG architectures, it represents the ratio of identified ground-truth facts in the context that were successfully synthesized into the final output, often involving a trade-off between exhaustive detail and response latency.
Distinguishes 'information coverage' from 'faithfulness' (hallucination-free) or 'relevance' (alignment with intent).
"A Jigsaw Puzzle: Ensuring every relevant piece found in the box (retrieved context) is actually placed on the table to reveal the full picture for the user."
- Recall(Prerequisite: Completeness is capped by the recall performance of the retrieval stage.)
- Faithfulness(Component: Together with completeness, it forms the 'RAG Triad' for evaluating response quality.)
- Context Adherence(Component: The constraint that limits completeness to only the provided retrieved data.)
Conceptual Overview
Completeness refers to the degree to which an LLM-generated response addresses all components of a user's query using the entirety of the relevant retrieved context. In RAG architectures, it represents the ratio of identified ground-truth facts in the context that were successfully synthesized into the final output, often involving a trade-off between exhaustive detail and response latency.
Disambiguation
Distinguishes 'information coverage' from 'faithfulness' (hallucination-free) or 'relevance' (alignment with intent).
Visual Analog
A Jigsaw Puzzle: Ensuring every relevant piece found in the box (retrieved context) is actually placed on the table to reveal the full picture for the user.