<｜begin▁of▁sentence｜>### Instruction:
Imagine you're designing an interactive storytelling experience, where the narrative unfolds as the user makes choices, branching the story in different directions. You've sketched a conceptual flow diagram for the storyline, where certain decisions lead the audience down various paths.

Now, you want to model this storyboard as a digital graph. Each decision point in the story is a node, and the narrative paths are the directed edges connecting these nodes. You've already outlined some of the storyline connections, which include the directed edges: from the beginning (node 0) to the first dilemma (node 1), from the beginning to an alternate path (node 2), each leading to further developments (nodes 3 and 4 respectively), and a climax point reached from one of the earlier developments (node 3 to node 5).

To simulate the user's journey through the first three steps of the story, you'd use a computational technique akin to building an oriented tree from a character's point of view, starting from the beginning of the tale. Specifically, you're interested in applying a Breadth-First Search (BFS) algorithm starting from node 0, restricting the exploration to a depth of 3 layers to keep the early part of the story focused.

What would the resulting graph look like for this segment of the audience's interactive experience? Keep in mind that this graph will not only help you visualize the possible narrative outcomes but also assist in programming the story's progression within the interactive medium.
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 4), (3, 5)])

# Perform a breadth-first search on the graph
source_node = 0
depth_limit = 3
bfs_oriented_tree = nx.bfs_tree(G, source=source_node, depth_limit=depth_limit)

# Print the edges of the BFS oriented tree
print(list(bfs_oriented_tree.edges()))
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