Spacy training - unable to recognize ents

Question

I have following code using Spacy. There are couple of training records to recognize simple set of text around destination.

def init_training_data ():

        nlp = spacy.blank('en')
        training_data = [
            ("Coliseum is visited by John Doe", [(0, 8, "DESTINATION"), (12, 19, "VISIT"), (23, 31, "TRAVELLER")]),
            ("John Doe has not been to Louvre", [(0, 8, "TRAVELLER"), (9, 21, "NOT_VISITED"), (25, 31, "DESTINATION")])]

        for text, annotations in training_data:
            doc = nlp(text)
            ents = []
            for start, end, label in annotations:
                span = doc.char_span(start, end, label=label)
                print (start, end, label)
                print (span)
                ents.append(span)
            print (ents)
            doc.ents = ents

        for itn in range(25):
            random.shuffle(training_data)
            for raw_text, entity_offsets in training_data:
                doc = nlp.make_doc(raw_text)
                example = Example.from_dict(doc, {"entities": entity_offsets})
                print (raw_text)
                nlp.update([example])
        
        text=nlp("Rome is visited by Fred Smith") 
        print (len(text.ents))
        for ents in text.ents: 
        # Print the document text and entitites 
            print(ents.text, ents.label_) 

The line print(len(text.ents)) returns 0 records. It should return 3, right? Can someone please point me in the right direction?