feat(classifier): add multilingual ECP inherence classifier POC

tests/test_benchmark_24.py

@@ -0,0 +1,71 @@
+"""Controlled 24-case benchmark suite for Multilingual NLP Entity Inherence Classifier.
+
+Matrix: 6 Languages (PT, EN, ES, DE, IT, FR) x 4 Decisions (DIRECT, CONTEXTUAL, TANGENTIAL, NOT_RELATED).
+Target Success Criterion: Precision >= 90% over the 24 cases.
+"""
+
+import json
+from pathlib import Path
+import pytest
+from src.models import ECPSnapshot, DecisionCategory
+from src.classifier import InherenceClassifier
+
+FIXTURES_DIR = Path(__file__).parent / "fixtures" / "benchmark_24"
+LANGUAGES = ["pt", "en", "es", "de", "it", "fr"]
+DECISION_TYPES = ["direct", "contextual", "tangential", "not_related"]
+
+BENCHMARK_CASES = [
+    (lang, dec_type)
+    for lang in LANGUAGES
+    for dec_type in DECISION_TYPES
+]
+
+
+@pytest.fixture(scope="module")
+def classifier():
+    return InherenceClassifier()
+
+
+@pytest.mark.parametrize("lang,dec_type", BENCHMARK_CASES)
+def test_benchmark_case(classifier, lang: str, dec_type: str):
+    case_dir = FIXTURES_DIR / lang
+    ecp_file = case_dir / "ecp.json"
+    content_file = case_dir / f"{dec_type}.md"
+    expected_file = case_dir / f"{dec_type}_expected.json"
+
+    assert ecp_file.is_file(), f"Missing ECP fixture: {ecp_file}"
+    assert content_file.is_file(), f"Missing Content fixture: {content_file}"
+    assert expected_file.is_file(), f"Missing Expected fixture: {expected_file}"
+
+    ecp = ECPSnapshot.from_json_str(ecp_file.read_text(encoding="utf-8"))
+    content = content_file.read_text(encoding="utf-8")
+    expected = json.loads(expected_file.read_text(encoding="utf-8"))
+
+    result = classifier.classify(ecp, content)
+
+    # 1. Decision category validation
+    assert (
+        result.decision.value == expected["expected_decision"]
+    ), f"[{lang.upper()} - {dec_type}] Expected {expected['expected_decision']}, got {result.decision.value}. Rationale: {result.rationale}"
+
+    # 2. Derived is_inherent boolean validation
+    assert (
+        result.is_inherent == expected["expected_is_inherent"]
+    ), f"[{lang.upper()} - {dec_type}] Expected is_inherent={expected['expected_is_inherent']}, got {result.is_inherent}"
+
+    # 3. Language detection validation
+    assert (
+        result.detected_language == expected["expected_language"]
+    ), f"[{lang.upper()} - {dec_type}] Expected language '{expected['expected_language']}', got '{result.detected_language}'"
+
+    # 4. Confidence threshold validation
+    min_conf = expected.get("min_confidence", 0.0)
+    assert (
+        result.confidence >= min_conf
+    ), f"[{lang.upper()} - {dec_type}] Expected confidence >= {min_conf}, got {result.confidence}"
+
+    # 5. Evidence presence for inherent content
+    if result.is_inherent:
+        assert (
+            len(result.evidence) > 0
+        ), f"[{lang.upper()} - {dec_type}] Inherent decision must have non-empty evidence snippets"