Replace personal pronoun with previous person mentioned (noisy coref)

Question

I want to do a noisy resolution such that given a personal prounoun, that pronoun is replace by the previous(nearest) person.

For example:

Alex is looking at buying a U.K. startup for $1 billion. He is very confident that this is going to happen. Sussan is also in the same situation. However, she has lost hope.

the output is:

Alex is looking at buying a U.K. startup for $1 billion. Alex is very confident that this is going to happen. Sussan is also in the same situation. However, Susan has lost hope.

Another example,

Peter is a friend of Gates. But Gates does not like him.

In this case, the output would be :

Peter is a friend of Gates. But Gates does not like Gates.

Yes! This is super noisy.

Using spacy: I have extracted the Person using NER, but how can I replace pronouns appropriately?

Code:

import spacy
nlp = spacy.load("en_core_web_sm")
for ent in doc.ents:
  if ent.label_ == 'PERSON':
    print(ent.text, ent.label_)

Answer 1

I have written a function that works for your two examples:

Consider using a larger model such as en_core_web_lg for more accurate tagging.

import spacy
from string import punctuation

nlp = spacy.load("en_core_web_lg")

def pronoun_coref(text):
    doc = nlp(text)
    pronouns = [(tok, tok.i) for tok in doc if (tok.tag_ == "PRP")]
    names = [(ent.text, ent[0].i) for ent in doc.ents if ent.label_ == 'PERSON']
    doc = [tok.text_with_ws for tok in doc]
    for p in pronouns:
        replace = max(filter(lambda x: x[1] < p[1], names),
                      key=lambda x: x[1], default=False)
        if replace:
            replace = replace[0]
            if doc[p[1] - 1] in punctuation:
                replace = ' ' + replace
            if doc[p[1] + 1] not in punctuation:
                replace = replace + ' '
            doc[p[1]] = replace
    doc = ''.join(doc)
    return doc