Multi-Context ScorerLLM-as-Judge

ContextFaithfulnessScorer

Enhanced faithfulness detection with fine-grained claim-by-claim analysis.

Overview

Enhanced faithfulness detection with fine-grained claim-by-claim analysis.

multi-contextrag

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

ParameterTypeRequiredDescription

Output Schema

FieldTypeDescription
scoreany-
passedany-
reasoningany-
metadataany-

Score Interpretation

9-10ExcellentResponse fully meets all evaluation criteria
7-8GoodResponse meets most criteria with minor issues
5-6FairResponse partially meets criteria, needs improvement
3-4PoorResponse has significant issues
0-2FailingResponse fails to meet basic criteria

Frequently Asked Questions

When should I use this scorer?

Use ContextFaithfulnessScorer 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 without a reference answer by using the specific input fields listed in its schema. Those fields are evidence for the check; they are not automatically factual ground truth.

Can I customize the threshold?

This scorer's displayed default threshold is 7. Where the eval-job configuration exposes a threshold, review it against the scorer's native scale before saving. The stored pass decision uses that scorer-specific configuration.

Quick Info

CategoryMulti-Context
Evaluation TypeLLM-as-Judge
Requires Expected OutputNo
Default Threshold7/10

Ready to try ContextFaithfulnessScorer?

Start evaluating your AI agents with Noveum.ai's comprehensive scorer library.

Explore More Scorers

Discover 112 published scorers across 15 categories: 82 Premium, 30 Free, 76 model-backed, and 36 dedicated voice and audio scorers