<｜begin▁of▁sentence｜>### Instruction:
Imagine you're at the central hub of emergency dispatch operations, a network where quick and efficient routes are critical to saving lives. You have a map in front of you that represents various routes and intersections that our emergency teams can take. On this map, certain intersections are connected by paths: there's a path between points 1 and 2, another between 1 and 3, one more connecting 2 and 3, and so on, as noted in the day's route log (similar to an edge list in a graph, with pairs such as (1, 2), (1, 3), (2, 3), (2, 4), (3, 4), (3, 5), (3, 6), (4, 5), (4, 6), (5, 6)). 

Our goal is to ensure that in the event of a complex emergency scenario that may affect multiple routes (consider this like a cycle in a graph), we have the most direct paths possible to avoid delays and ensure rapid response. In technical terms, we're reviewing the map to verify that for all possible detours (cycles of length at least four), we've got direct shortcuts (chords) that allow faster access, bypassing the traditional route if needed.

Your task is to examine the connections (edges) in our daily route log and determine if our network of paths allows for these direct shortcuts, which would mean it's a well-designed system (chordal) for emergency scenarios. This confirmation will help us guarantee the efficiency and swiftness of our emergency response.
### Response:
import networkx as nx

def check_if_chordal(edges):
    G = nx.Graph()
    G.add_edges_from(edges)
    return nx.is_chordal(G)

edges = [
    (1, 2),
    (1, 3),
    (2, 3),
    (2, 4),
    (3, 4),
    (3, 5),
    (3, 6),
    (4, 5),
    (4, 6),
    (5, 6),
]

is_chordal_graph = check_if_chordal(edges)
print('Is the graph chordal:', is_chordal_graph)
<|EOT|>
