diff --git a/README.md b/README.md
index 31c03bff..fa227c60 100644
--- a/README.md
+++ b/README.md
@@ -1142,77 +1142,6 @@ When merging entities:
 
 </details>
 
-## Entity Merging
-
-<details>
-<summary> <b>Merge Entities and Their Relationships</b> </summary>
-
-LightRAG now supports merging multiple entities into a single entity, automatically handling all relationships:
-
-```python
-# Basic entity merging
-rag.merge_entities(
-    source_entities=["Artificial Intelligence", "AI", "Machine Intelligence"],
-    target_entity="AI Technology"
-)
-```
-
-With custom merge strategy:
-
-```python
-# Define custom merge strategy for different fields
-rag.merge_entities(
-    source_entities=["John Smith", "Dr. Smith", "J. Smith"],
-    target_entity="John Smith",
-    merge_strategy={
-        "description": "concatenate",  # Combine all descriptions
-        "entity_type": "keep_first",   # Keep the entity type from the first entity
-        "source_id": "join_unique"     # Combine all unique source IDs
-    }
-)
-```
-
-With custom target entity data:
-
-```python
-# Specify exact values for the merged entity
-rag.merge_entities(
-    source_entities=["New York", "NYC", "Big Apple"],
-    target_entity="New York City",
-    target_entity_data={
-        "entity_type": "LOCATION",
-        "description": "New York City is the most populous city in the United States.",
-    }
-)
-```
-
-Advanced usage combining both approaches:
-
-```python
-# Merge company entities with both strategy and custom data
-rag.merge_entities(
-    source_entities=["Microsoft Corp", "Microsoft Corporation", "MSFT"],
-    target_entity="Microsoft",
-    merge_strategy={
-        "description": "concatenate",  # Combine all descriptions
-        "source_id": "join_unique"     # Combine source IDs
-    },
-    target_entity_data={
-        "entity_type": "ORGANIZATION",
-    }
-)
-```
-
-When merging entities:
-
-* All relationships from source entities are redirected to the target entity
-* Duplicate relationships are intelligently merged
-* Self-relationships (loops) are prevented
-* Source entities are removed after merging
-* Relationship weights and attributes are preserved
-
-</details>
-
 ## Multimodal Document Processing (RAG-Anything Integration)
 
 LightRAG now seamlessly integrates with [RAG-Anything](https://github.com/HKUDS/RAG-Anything), a comprehensive **All-in-One Multimodal Document Processing RAG system** built specifically for LightRAG. RAG-Anything enables advanced parsing and retrieval-augmented generation (RAG) capabilities, allowing you to handle multimodal documents seamlessly and extract structured content—including text, images, tables, and formulas—from various document formats for integration into your RAG pipeline.