diff --git a/lightrag/operate.py b/lightrag/operate.py
index 97a356ad..ee5dd469 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -106,6 +106,8 @@ async def _handle_entity_relation_summary(
     entity_or_relation_name: str,
     description: str,
     global_config: dict,
+    pipeline_status: dict = None,
+    pipeline_status_lock=None,
 ) -> str:
     """Handle entity relation summary
     For each entity or relation, input is the combined description of already existing description and new description.
@@ -122,6 +124,14 @@ async def _handle_entity_relation_summary(
     tokens = encode_string_by_tiktoken(description, model_name=tiktoken_model_name)
     if len(tokens) < summary_max_tokens:  # No need for summary
         return description
+
+    # Update pipeline status when LLM summary is needed
+    status_message = "Use LLM to re-summary description..."
+    logger.info(status_message)
+    if pipeline_status is not None and pipeline_status_lock is not None:
+        async with pipeline_status_lock:
+            pipeline_status["latest_message"] = status_message
+            pipeline_status["history_messages"].append(status_message)
     prompt_template = PROMPTS["summarize_entity_descriptions"]
     use_description = decode_tokens_by_tiktoken(
         tokens[:llm_max_tokens], model_name=tiktoken_model_name
@@ -212,6 +222,8 @@ async def _merge_nodes_then_upsert(
     nodes_data: list[dict],
     knowledge_graph_inst: BaseGraphStorage,
     global_config: dict,
+    pipeline_status: dict = None,
+    pipeline_status_lock=None,
 ):
     """Get existing nodes from knowledge graph use name,if exists, merge data, else create, then upsert."""
     already_entity_types = []
@@ -221,6 +233,14 @@ async def _merge_nodes_then_upsert(
 
     already_node = await knowledge_graph_inst.get_node(entity_name)
     if already_node is not None:
+        # Update pipeline status when a node that needs merging is found
+        status_message = f"Merging entities: {entity_name}"
+        logger.info(status_message)
+        if pipeline_status is not None and pipeline_status_lock is not None:
+            async with pipeline_status_lock:
+                pipeline_status["latest_message"] = status_message
+                pipeline_status["history_messages"].append(status_message)
+
         already_entity_types.append(already_node["entity_type"])
         already_source_ids.extend(
             split_string_by_multi_markers(already_node["source_id"], [GRAPH_FIELD_SEP])
@@ -249,7 +269,7 @@ async def _merge_nodes_then_upsert(
 
     logger.debug(f"file_path: {file_path}")
     description = await _handle_entity_relation_summary(
-        entity_name, description, global_config
+        entity_name, description, global_config, pipeline_status, pipeline_status_lock
     )
     node_data = dict(
         entity_id=entity_name,
@@ -272,6 +292,8 @@ async def _merge_edges_then_upsert(
     edges_data: list[dict],
     knowledge_graph_inst: BaseGraphStorage,
     global_config: dict,
+    pipeline_status: dict = None,
+    pipeline_status_lock=None,
 ):
     already_weights = []
     already_source_ids = []
@@ -280,6 +302,14 @@ async def _merge_edges_then_upsert(
     already_file_paths = []
 
     if await knowledge_graph_inst.has_edge(src_id, tgt_id):
+        # Update pipeline status when an edge that needs merging is found
+        status_message = f"Merging edges: {src_id} - {tgt_id}"
+        logger.info(status_message)
+        if pipeline_status is not None and pipeline_status_lock is not None:
+            async with pipeline_status_lock:
+                pipeline_status["latest_message"] = status_message
+                pipeline_status["history_messages"].append(status_message)
+
         already_edge = await knowledge_graph_inst.get_edge(src_id, tgt_id)
         # Handle the case where get_edge returns None or missing fields
         if already_edge:
@@ -358,7 +388,11 @@ async def _merge_edges_then_upsert(
                 },
             )
     description = await _handle_entity_relation_summary(
-        f"({src_id}, {tgt_id})", description, global_config
+        f"({src_id}, {tgt_id})",
+        description,
+        global_config,
+        pipeline_status,
+        pipeline_status_lock,
     )
     await knowledge_graph_inst.upsert_edge(
         src_id,
@@ -613,7 +647,12 @@ async def extract_entities(
             # Process and update entities
             for entity_name, entities in maybe_nodes.items():
                 entity_data = await _merge_nodes_then_upsert(
-                    entity_name, entities, knowledge_graph_inst, global_config
+                    entity_name,
+                    entities,
+                    knowledge_graph_inst,
+                    global_config,
+                    pipeline_status,
+                    pipeline_status_lock,
                 )
                 chunk_entities_data.append(entity_data)
 
@@ -627,6 +666,8 @@ async def extract_entities(
                     edges,
                     knowledge_graph_inst,
                     global_config,
+                    pipeline_status,
+                    pipeline_status_lock,
                 )
                 chunk_relationships_data.append(edge_data)