diff --git a/trustgraph-flow/trustgraph/extract/kg/ontology/extract.py b/trustgraph-flow/trustgraph/extract/kg/ontology/extract.py
index 7e474855..1f389e25 100644
--- a/trustgraph-flow/trustgraph/extract/kg/ontology/extract.py
+++ b/trustgraph-flow/trustgraph/extract/kg/ontology/extract.py
@@ -83,7 +83,7 @@ class Processor(FlowProcessor):
 
         # Configuration
         self.top_k = params.get("top_k", 10)
-        self.similarity_threshold = params.get("similarity_threshold", 0.7)
+        self.similarity_threshold = params.get("similarity_threshold", 0.3)
 
         # Track loaded ontology version
         self.current_ontology_version = None
@@ -272,13 +272,15 @@ class Processor(FlowProcessor):
                         f"{len(ontology_subset.object_properties)} object properties, "
                         f"{len(ontology_subset.datatype_properties)} datatype properties")
 
-            # Build extraction prompt
-            prompt = self.build_extraction_prompt(chunk, ontology_subset)
+            # Build extraction prompt variables
+            prompt_variables = self.build_extraction_variables(chunk, ontology_subset)
 
             # Call prompt service for extraction
             try:
-                triples_response = await flow("prompt-request").extract_ontology_triples(
-                    prompt=prompt
+                # Use prompt() method with extract-with-ontologies prompt ID
+                triples_response = await flow("prompt-request").prompt(
+                    id="extract-with-ontologies",
+                    variables=prompt_variables
                 )
                 logger.debug(f"Extraction response: {triples_response}")
 
@@ -477,8 +479,8 @@ TRIPLES (JSON array):"""
         parser.add_argument(
             '--similarity-threshold',
             type=float,
-            default=0.7,
-            help='Similarity threshold for ontology matching (default: 0.7)'
+            default=0.3,
+            help='Similarity threshold for ontology matching (default: 0.3, range: 0.0-1.0)'
         )
         FlowProcessor.add_args(parser)
 
diff --git a/trustgraph-flow/trustgraph/extract/kg/ontology/ontology_selector.py b/trustgraph-flow/trustgraph/extract/kg/ontology/ontology_selector.py
index d76f585e..6b493ea2 100644
--- a/trustgraph-flow/trustgraph/extract/kg/ontology/ontology_selector.py
+++ b/trustgraph-flow/trustgraph/extract/kg/ontology/ontology_selector.py
@@ -84,22 +84,20 @@ class OntologySelector:
         # Check if vector store has any elements
         vector_store = self.embedder.get_vector_store()
         store_size = vector_store.size()
-        logger.debug(f"Vector store size: {store_size} elements")
+        logger.info(f"Vector store size: {store_size} elements")
 
         if store_size == 0:
             logger.warning("Vector store is empty - no ontology elements embedded")
             return relevant_elements
 
-        # Process each segment
-        for segment in segments:
+        # Process each segment (log first few for debugging)
+        for i, segment in enumerate(segments):
             # Get embedding for segment
             embedding = await self.embedder.embed_text(segment.text)
             if embedding is None:
                 logger.warning(f"Failed to embed segment: {segment.text[:50]}...")
                 continue
 
-            logger.debug(f"Searching for segment: {segment.text[:100]}... (embedding shape: {embedding.shape})")
-
             # Search vector store with no threshold to see all scores
             all_results = vector_store.search(
                 embedding=embedding,
@@ -107,16 +105,17 @@ class OntologySelector:
                 threshold=0.0  # Get all results to see scores
             )
 
-            # Log top scores for debugging
-            if all_results:
+            # Log top scores for first 3 segments to debug
+            if i < 3 and all_results:
                 top_scores = [r.score for r in all_results[:3]]
-                logger.debug(f"Top 3 scores for segment: {top_scores}, threshold={self.similarity_threshold}")
+                top_elements = [r.metadata['element'] for r in all_results[:3]]
+                logger.info(f"Segment {i}: '{segment.text[:60]}...'")
+                logger.info(f"  Top 3 scores: {top_scores} (threshold={self.similarity_threshold})")
+                logger.info(f"  Top 3 elements: {top_elements}")
 
             # Filter by threshold
             results = [r for r in all_results if r.score >= self.similarity_threshold]
 
-            logger.debug(f"Found {len(results)} results above threshold (out of {len(all_results)} total)")
-
             # Process results
             for result in results:
                 metadata = result.metadata