<｜begin▁of▁sentence｜>### Instruction:
In the context of conducting due diligence for a case involving complex network structures, counsel has requested that we initiate a cursory examination of two distinct types of legal relationships. Specifically, we are to conceptualize a simple network map composed of five distinct entities without any existing connections; this will serve as a foundational framework for our primary graph.

Simultaneously, we are instructed to prepare an illustrative MultiGraph model mirroring the primary graph's entity framework, which permits the documentation and visualization of multiple relationships between the same pair of entities, should such complexities arise in the case. This redundancy-enabled graph is envisioned as a tool to better understand potential overlapping legal interactions or claims among the involved parties.

Upon establishing these rudimentary network structures, we are required to produce a tabulation reflecting the counts of entities (nodes) and connections (edges) within both the basic graph and the MultiGraph. These figures will be employed to verify the initial state of these graphs - confirming the absence of connections prior to our detailed analysis. This preparatory step will ensure accuracy and clarity as we proceed to meticulously map the intricate web of legal relations pertinent to the case at hand.
### Response:
import networkx as nx

# Create an empty graph with 5 nodes
G = nx.empty_graph(5)

# Create an empty graph using a different constructor
H = nx.empty_graph(5, create_using=nx.MultiGraph)

# Print the number of nodes and edges in G
print('Graph G - Nodes:', G.number_of_nodes())
print('Graph G - Edges:', G.number_of_edges())

# Print the number of nodes and edges in H
print('MultiGraph H - Nodes:', H.number_of_nodes())
print('MultiGraph H - Edges:', H.number_of_edges())
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