# EVALUATOR Spans
## Purpose
EVALUATOR spans represent quality assessment operations (answer relevance, faithfulness, hallucination detection).
## Required Attributes
| Attribute | Type | Description | Required |
|-----------|------|-------------|----------|
| `openinference.span.kind` | String | Must be "EVALUATOR" | Yes |
## Common Attributes
| Attribute | Type | Description |
|-----------|------|-------------|
| `input.value` | String | Content being evaluated |
| `output.value` | String | Evaluation result (score, label, explanation) |
| `metadata.evaluator_name` | String | Evaluator identifier |
| `metadata.score` | Float | Numeric score (0-1) |
| `metadata.label` | String | Categorical label (relevant/irrelevant) |
## Example: Answer Relevance
```json
{
"openinference.span.kind": "EVALUATOR",
"input.value": "{\"question\": \"What is the capital of France?\", \"answer\": \"The capital of France is Paris.\"}",
"input.mime_type": "application/json",
"output.value": "0.95",
"metadata.evaluator_name": "answer_relevance",
"metadata.score": 0.95,
"metadata.label": "relevant",
"metadata.explanation": "Answer directly addresses the question with correct information"
}
```
## Example: Faithfulness Check
```json
{
"openinference.span.kind": "EVALUATOR",
"input.value": "{\"context\": \"Paris is in France.\", \"answer\": \"Paris is the capital of France.\"}",
"input.mime_type": "application/json",
"output.value": "0.5",
"metadata.evaluator_name": "faithfulness",
"metadata.score": 0.5,
"metadata.label": "partially_faithful",
"metadata.explanation": "Answer makes unsupported claim about Paris being the capital"
}
```
