diff --git a/cognee/modules/data/extraction/knowledge_graph/extract_content_graph_sequential.py b/cognee/modules/data/extraction/knowledge_graph/extract_content_graph_sequential.py
index 42c242490..092a239ac 100644
--- a/cognee/modules/data/extraction/knowledge_graph/extract_content_graph_sequential.py
+++ b/cognee/modules/data/extraction/knowledge_graph/extract_content_graph_sequential.py
@@ -27,7 +27,7 @@ async def extract_content_graph_sequential(
         edges_json = json.dumps([e.model_dump() for e in current_edges], ensure_ascii=False)
 
         graph_user = render_prompt(
-            graph_user_prompt_path,
+            graph_user_prompt_path,  #:TODO: this could use some formatting due to html #34 codes.
             {
                 "text": content,
                 "graph": f"nodes: {nodes_json}, edges: {edges_json}",
diff --git a/cognee/modules/data/extraction/knowledge_graph/extract_content_node_edge_multi_sequential.py b/cognee/modules/data/extraction/knowledge_graph/extract_content_node_edge_multi_sequential.py
new file mode 100644
index 000000000..4336c6b65
--- /dev/null
+++ b/cognee/modules/data/extraction/knowledge_graph/extract_content_node_edge_multi_sequential.py
@@ -0,0 +1,57 @@
+import json
+
+from cognee.infrastructure.llm.get_llm_client import get_llm_client
+from cognee.infrastructure.llm.prompts import render_prompt
+from cognee.shared.data_models import KnowledgeGraph, NodeList, EdgeList
+
+
+async def extract_content_node_edge_multi_sequential(
+    content: str, node_rounds: int = 2, edge_rounds=2
+):
+    llm_client = get_llm_client()
+
+    current_nodes = NodeList()
+
+    for pass_idx in range(node_rounds):
+        nodes_json = json.dumps([n.model_dump() for n in current_nodes.nodes], ensure_ascii=False)
+
+        node_system = render_prompt("node_extraction_prompt_sequential.txt", {})
+        node_user = render_prompt(
+            "node_extraction_prompt_sequential_user.txt",
+            {
+                "text": content,
+                "nodes": {nodes_json},
+                "total_rounds": {node_rounds},
+                "round_number": {pass_idx},
+            },
+        )
+
+        current_nodes = await llm_client.acreate_structured_output(node_user, node_system, NodeList)
+
+    final_nodes = current_nodes
+    final_nodes_json = json.dumps([n.model_dump() for n in final_nodes.nodes], ensure_ascii=False)
+
+    current_edges = EdgeList()
+
+    for pass_idx in range(edge_rounds):
+        edges_json = json.dumps([n.model_dump() for n in current_edges.edges], ensure_ascii=False)
+
+        edges_system = render_prompt("edge_extraction_prompt_sequential.txt", {})
+        edges_user = render_prompt(
+            "edge_extraction_prompt_sequential_user.txt",
+            {
+                "text": content,
+                "nodes": {final_nodes_json},
+                "edges": {edges_json},
+                "total_rounds": {node_rounds},
+                "round_number": {pass_idx},
+            },
+        )
+
+        current_edges = await llm_client.acreate_structured_output(
+            edges_user, edges_system, EdgeList
+        )
+
+    final_edges = current_edges
+
+    return KnowledgeGraph(nodes=final_nodes.nodes, edges=final_edges.edges)
diff --git a/cognee/tasks/graph/extract_graph_from_data.py b/cognee/tasks/graph/extract_graph_from_data.py
index 58b2502a2..252467e0c 100644
--- a/cognee/tasks/graph/extract_graph_from_data.py
+++ b/cognee/tasks/graph/extract_graph_from_data.py
@@ -10,13 +10,18 @@ from cognee.modules.chunking.models.DocumentChunk import DocumentChunk
 from cognee.modules.data.extraction.knowledge_graph.extract_content_graph import (
     extract_content_graph,
 )
-from cognee.modules.data.extraction.knowledge_graph.extract_content_graph_multi_parallel import (
-    extract_content_graph_multi_parallel,
+from cognee.modules.data.extraction.knowledge_graph.extract_content_node_edge_multi_parallel import (
+    extract_content_node_edge_multi_parallel,
 )
 
 from cognee.modules.data.extraction.knowledge_graph.extract_content_graph_sequential import (
     extract_content_graph_sequential,
 )
+
+from cognee.modules.data.extraction.knowledge_graph.extract_content_node_edge_multi_sequential import (
+    extract_content_node_edge_multi_sequential,
+)
+
 from cognee.modules.graph.utils import (
     expand_with_nodes_and_edges,
     retrieve_existing_edges,
@@ -70,11 +75,16 @@ async def extract_graph_from_data(
     """
     chunk_graphs = await asyncio.gather(
         # *[extract_content_graph(chunk.text, graph_model) for chunk in data_chunks]
-        # *[extract_content_graph_multi_parallel(chunk.text, graph_model) for chunk in data_chunks]
-        *[extract_content_graph_sequential(chunk.text, graph_model) for chunk in data_chunks]
+        # *[extract_content_node_edge_multi_parallel(content=chunk.text, node_rounds=2) for chunk in data_chunks]
+        # *[extract_content_graph_sequential(content=chunk.text, response_model=graph_model, graph_extraction_rounds=2) for chunk in data_chunks]
+        *[
+            extract_content_node_edge_multi_sequential(
+                content=chunk.text, node_rounds=1, edge_rounds=1
+            )
+            for chunk in data_chunks
+        ]
     )
 
-    # Note: Filter edges with missing source or target nodes
     if graph_model == KnowledgeGraph:
         for graph in chunk_graphs:
             valid_node_ids = {node.id for node in graph.nodes}