Harden spaCy NER fallback in semantic extract

CHANGELOG.md

@@ -7,6 +7,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+- **spaCy Runtime Fallback for NER Benchmarks**:
+    - Hardened `NERExtractor` spaCy initialization so installed-but-broken spaCy environments no longer crash during extractor construction.
+    - Updated ML entity extraction fallback behavior to catch runtime spaCy initialization failures, not just missing-model errors.
+    - Added regression coverage for the "spaCy present but unusable at runtime" initialization path.
+
 ### Added
 - **Configurable LLM Retry Logic**:
     - Exposed `max_retries` parameter in `NERExtractor`, `RelationExtractor`, `TripletExtractor` and low-level extraction methods (`extract_entities_llm`, `extract_relations_llm`, `extract_triplets_llm`).

semantica/semantic_extract/methods.py

@@ -683,6 +683,16 @@ def extract_entities_ml(
                 "spaCy model not available, falling back to pattern extraction"
             )
             return extract_entities_pattern(text, **kwargs)
+        except Exception as exc:
+            logger.warning(
+                f"spaCy model failed to initialize ({exc}), falling back to pattern extraction"
+            )
+            return extract_entities_pattern(text, **kwargs)
+    except Exception as exc:
+        logger.warning(
+            f"spaCy model {model} failed to initialize ({exc}), falling back to pattern extraction"
+        )
+        return extract_entities_pattern(text, **kwargs)
 
     doc = nlp(text)
     entities = []

semantica/semantic_extract/ner_extractor.py

@@ -154,6 +154,10 @@ class NERExtractor:
                 self.logger.warning(
                     f"spaCy model {self.model_name} not found. ML method will fallback."
                 )
+            except Exception as exc:
+                self.logger.warning(
+                    f"spaCy model {self.model_name} failed to initialize ({exc}). ML method will fallback."
+                )
 
     def extract(self, text: Union[str, List[Dict[str, Any]], List[str]], pipeline_id: Optional[str] = None, **kwargs) -> Union[List[Entity], List[List[Entity]]]:
         """

tests/test_ner_configurations.py

@@ -101,6 +101,16 @@ class TestNERConfigurations(unittest.TestCase):
             self.assertEqual(entities[0].metadata["extraction_method"], "ml")
             self.assertEqual(entities[0].metadata["model"], "en_core_web_trf")
 
+    @patch('semantica.semantic_extract.ner_extractor.spacy')
+    def test_ner_ml_init_falls_back_when_spacy_runtime_is_broken(self, mock_spacy):
+        """Test NER init does not crash when spaCy is installed but unusable at runtime."""
+        mock_spacy.load.side_effect = RuntimeError("ConfigSchemaNlp is not fully defined")
+
+        with patch('semantica.semantic_extract.ner_extractor.SPACY_AVAILABLE', True):
+            extractor = NERExtractor(method="ml", model="en_core_web_sm")
+
+        self.assertIsNone(extractor.nlp)
+
     def test_ner_regex_config(self):
         """Test NER with Regex configuration"""
         print("\nTesting NER with Regex configuration...")