ContextConsistencyScorer
Evaluates consistency of an answer across multiple context chunks. Identifies cases where the answer may be faithful to some contexts but inconsistent with others.
Overview
Evaluates consistency of an answer across multiple context chunks. Identifies cases where the answer may be faithful to some contexts but inconsistent with others.
Use Cases
- RAG-based question answering systems
How It Works
This scorer uses LLM-as-Judge technology to evaluate responses. It prompts a large language model with specific evaluation criteria and the content to assess, then analyzes the LLM's judgment to produce a score and detailed reasoning.
Input Schema
| Parameter | Type | Required | Description |
|---|---|---|---|
| output_text | str | Yes | Answer to check for consistency |
| input_text | str | Yes | Original question |
| context | list[str] | Yes | Multiple context chunks |
Output Schema
| Field | Type | Description |
|---|---|---|
| score | float | Consistency score (0-10) |
| passed | bool | True if consistent |
| reasoning | str | Consistency analysis |
| metadata.consistency_scores | dict | Per-chunk consistency |
Score Interpretation
Default threshold: 7/10
Related Scorers
Frequently Asked Questions
When should I use this scorer?
Use ContextConsistencyScorer when you need to evaluate multi-context and rag aspects of your AI outputs. It's particularly useful for rag-based question answering systems.
Why doesn't this scorer need expected output?
This scorer evaluates quality aspects that don't require comparison against a reference answer. It uses the system prompt and context as the implicit ground truth.
Can I customize the threshold?
Yes, the default threshold of 7 can be customized when configuring the scorer.
Quick Info
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