---
title: "Evals Module"
description: "Evaluation framework for measuring Knowledge Graph quality, extraction accuracy, and pipeline performance — coming soon."
icon: "chart-line"
---
`semantica.evals` is planned as a comprehensive evaluation framework for measuring extraction accuracy, graph quality, and pipeline performance.
**`semantica.evals` is not yet implemented.** The module exists as a placeholder (`__all__ = []`). No classes or functions are available for import. This page describes the planned API.
## Planned Features
When released, `semantica.evals` will provide:
| Planned Class | Role |
| --- | --- |
| `KGEvaluator` | Completeness, consistency, schema compliance, coverage, and orphan node detection |
| `ExtractionEvaluator` | NER precision / recall / F1 and relation extraction metrics against gold datasets |
| `PipelineBenchmark` | Throughput (docs/sec), per-step latency, peak memory, and error rate |
| `RegressionTracker` | Record runs and compare metrics across commits or config changes |
| `EvalReport` | Structured report: `{scores, regressions, recommendations}` |
| `DeduplicationEvaluator` | Merge precision, false positive / false negative rates |
| `ReasoningEvaluator` | Inference accuracy, rule coverage, and derivation depth |
## Current Workaround
Until `semantica.evals` ships, use `semantica.ontology.OntologyEvaluator` for ontology quality metrics:
```python
from semantica.ontology import OntologyEvaluator
evaluator = OntologyEvaluator()
report = evaluator.evaluate(ontology, kg)
print(f"Coverage: {report.coverage:.2%}")
print(f"Completeness: {report.completeness:.2%}")
```
Extraction module.
Graph quality assessment.
Pipeline performance metrics.
Available now for ontology quality metrics.