Hmm. Actually that code looks weird. Try this:
text = content
doc = nlp.make_doc(text)
(beams, somethingelse) = nlp.entity.beam_parse([doc], beam_width=16, beam_density=0.0001)
for score, ents in nlp.entity.moves.get_beam_parses(beams[0]):
print (score, ents)
entity_scores = defaultdict(float)
for start, end, label in ents:
# print ("here")
entity_scores[(start, end, label)] += score
print ('entity_scores', entity_scores)