<｜begin▁of▁sentence｜>### Instruction:
Imagine that we are constructing a linguistic map to represent the paths of communication between different language communities, which are symbolically represented by nodes in our network. Our edges in the graph denote the direct interactions between these communities.

Currently, our graph is defined by the connections: [('A', 'B'), ('B', 'C'), ('B', 'D'), ('A', 'E'), ('E', 'F')]. In this scenario, community 'B' has decided to undergo a period of linguistic isolation for a cultural festival. During this time, it is important for our map to reflect this change; therefore, we need to generate a subgraph where all pathways—edges—involving community 'B' are temporarily removed, signifying the cessation of their communications with other groups.

How might we process our linguistic network to visualize this period of isolation by creating a new subgraph that excludes the interactive pathways of community 'B', while preserving the rest of the network structure? This adjustment will ensure that our map remains an accurate tool for understanding the dynamic communication landscape among the language communities.
### Response:
import networkx as nx

# Define a function to filter edges
def filter_edge(n1, n2):
    return (n1, n2) if n1 != 'B' else None

# Create a graph
G = nx.Graph()
G.add_edges_from([('A', 'B'), ('B', 'C'), ('B', 'D'), ('A', 'E'), ('E', 'F')])

# Create a subgraph based on the filter
filtered_G = nx.subgraph_view(G, filter_edge=filter_edge)

# Display edges of the filtered graph
print(list(filtered_G.edges()))
<|EOT|>
