Convert multirelational graphs to bipartite graphs with networkx

I have a multi-relational graph G (subject s and object o nodes connected with an edge having a predicate label p), made with networkx.DiGraph. Is there a way to easily and elegantly create its bipartite graph by replacing each labeled edge (s, p, o) with two unlabeled edges {(s,p),(p,o)}? This operation is also called Levi transformation (Levi, 1942) and is aimed to treat each entity and relation equally.

Current graph construction example:

amr_graph = networkx.DiGraph()

for node_id, node_string in amr.nodes.items():
   amr_graph.add_node(node_id, name=node_string)

for subj, pred, obj in amr.edges:
   amr_graph.add_edge(subj, obj, key=pred)

Just create the new edges as you see fit:

import random
import networkx as nx

s=[random.randint(0,2) for i in range(10)]
o=[random.randint(3,5) for i in range(10)]
p=[random.randint(6,8) for i in range(10)]

G = nx.DiGraph()
H = nx.DiGraph()
F = nx.DiGraph()

#split while constructing the orgiginal graph
for subj, pred, obj in zip(s,p,o):
    G.add_edge(subj, obj, key= pred)

    H.add_edge(subj, pred, key = obj)
    H.add_edge(pred, obj, key= subj)
               
#use existing graph to split edges              
for subj, obj, d in G.edges(data=True):
    pred = d['key']

    F.add_edge(subj, pred, key = obj)
    F.add_edge(pred, obj, key= subj)