<｜begin▁of▁sentence｜>### Instruction:
Imagine we're in the midst of designing an immersive new video game that revolves around complex relationships and networks within a dynamic game world. Our programmers have provided us with a JSON file that contains the intricate map of these relationships, including key information about the in-game entities and the paths that connect them, all labeled with important attributes for gameplay.

To breathe life into this virtual universe, we must translate this JSON structure into a usable form within our game design tools. Picture the JSON as the blueprint for a vast network of interactions, where nodes represent characters or points of interest, and edges symbolize the possible routes or connections between them, each with their own set of characteristics vital to the game experience.

Our task is to utilize NetworkX's node_link_graph method to accurately reconstruct this interconnected web as a graph within our development environment. This graph must retain all the rich label data embedded in the JSON, since it's essential for dictating the nuances of our game's interactive narrative and mechanics.

How can we craft this conversion so that the graph not only reflects the structural complexity of our JSON blueprint but also preserves the detailed labels on nodes and edges, ensuring that these attributes seamlessly integrate into the attributes of our NetworkX graph? This step is crucial for ensuring that the relationships and pathways in our digital world carry the intended narrative weight and gameplay significance.

Let's confer on the potential approach to achieve this, keeping in mind that the authenticity and depth of our game world hinges on a flawless implementation of these labels within the reconstructed network.
### Response:
import networkx as nx
import json

# Here is a JSON object representing a graph
graph_json = '{"directed": false, "multigraph": false, "graph": {}, "nodes": [{"id": "A", "label": "Alpha"}, {"id": "B", "label": "Beta"}], "links": [{"source": "A", "target": "B", "label": "connects to"}]}'

# Convert the JSON string to a Python dictionary
graph_data = json.loads(graph_json)

# Use the node_link_graph function to create a NetworkX graph from the dictionary
G = nx.node_link_graph(graph_data)

# Display edges of the graph (and nodes, if needed)
print('Nodes:', G.nodes(data=True))
print('Edges:', G.edges(data=True))
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