<｜begin▁of▁sentence｜>### Instruction:
Given a graph whose edge set is [('A', 'B', 1), ('A', 'C', 3), ('B', 'C', 2), ('C', 'D', 5), ('B', 'D', 4)], with the weights representing the edge weights, how can you use NetworkX to find the edges that make up the maximum spanning tree using Kruskal's algorithm?
### Response:
import networkx as nx
from networkx.algorithms import tree

# Create a weighted graph
G = nx.Graph()
G.add_edge('A', 'B', weight=1)
G.add_edge('A', 'C', weight=3)
G.add_edge('B', 'C', weight=2)
G.add_edge('C', 'D', weight=5)
G.add_edge('B', 'D', weight=4)

# Find maximum spanning edges by Kruskal's algorithm
mst_edges = tree.maximum_spanning_edges(G, algorithm="kruskal", data=False)

# Convert the iterator to a list of edges
edge_list = list(mst_edges)

# Display the edges in the maximum spanning tree
print(sorted(edge_list))
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