--- 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.