LLM Answer Match Evaluator

The LLM Answer Match Evaluator is a specialized component that compares generated responses against expected outputs to determine their semantic similarity and correctness. It helps ensure that generated answers align with expected responses while accounting for variations in expression.

LLM Answer Match Evaluator interface and configuration

Usage Note: The evaluator focuses on semantic matching rather than exact text matching. It can handle variations in wording while still identifying matching content and meaning.

Component Inputs

Input Text: The original query or context
Example: "What is the capital of France?"
Generated Output: The answer to evaluate
Example: "The capital city of France is Paris"
Expected Output: The expected answer
Example: "Paris is France's capital"
LLM Model: The language model to use for evaluation
Example: "gpt-4", "claude-2"

Component Outputs

Match Score: Similarity score between generated and expected output
Example: 0.95 (95% match)
Match Details: Specific aspects of matching and differences
Detailed breakdown of matching elements
Suggestions: Potential improvements for better matching
Recommendations for improving match accuracy

How It Works

The LLM Answer Match Evaluator uses advanced semantic comparison techniques to evaluate the similarity between generated and expected responses, considering various aspects such as content, context, and meaning.

Evaluation Process

Semantic parsing of inputs
Content comparison
Context analysis
Similarity scoring
Match detail generation
Suggestion compilation

Use Cases

Answer Validation: Verify response accuracy
Quality Assurance: Ensure response quality
Training Data Validation: Verify training examples
Response Improvement: Identify areas for enhancement
Automated Testing: Test response accuracy at scale

Implementation Example

const answerMatchEvaluator = new LLMAnswerMatchEvaluator({
  inputText: "What is the capital of France?",
  generatedOutput: "The capital city of France is Paris",
  expectedOutput: "Paris is France's capital",
  llmModel: "gpt-4"
});

const result = await answerMatchEvaluator.evaluate();

// Output:
// {
//   matchScore: 0.95,
//   matchDetails: {
//     contentMatch: true,
//     contextMatch: true,
//     variations: ["word order", "phrasing"]
//   },
//   suggestions: ["Response is semantically equivalent"]
// }

Additional Resources

Best Practices

Provide clear expected outputs
Consider semantic variations
Use appropriate matching thresholds
Include relevant context
Review match details thoroughly

Documentation