Splitting compound sentences to a set of simple sentences using spaCy package

compound_to_simple.py

import spacy
nlp = spacy.load('en_core_web_md')

def compound_to_simple(sentence):
    doc = nlp(sentence)
    
    root_token = None
    for token in doc:
        if (token.dep_ == "ROOT"):
            root_token = token
            
    other_verbs = []
    for token in doc:
        ancestors = list(token.ancestors)
        if (token.pos_ == "VERB" and len(ancestors) < 3 and token != root_token):
            other_verbs.append(token)
            
    token_spans = []
    all_verbs = [root_token] + other_verbs
    for other_verb in all_verbs:
        first_token_index = len(doc)
        last_token_index = 0
        this_verb_children = list(other_verb.children)
        for child in this_verb_children:
            if (child not in all_verbs):
                if (child.i < first_token_index):
                    first_token_index = child.i
                if (child.i > last_token_index):
                    last_token_index = child.i
        token_spans.append((first_token_index, last_token_index))
        
    sentence_clauses = []
    for token_span in token_spans:
        start = token_span[0]
        end = token_span[1]
        if (start < end):
            clause = doc[start:end]
            sentence_clauses.append(clause)
    sentence_clauses = sorted(sentence_clauses, key=lambda tup: tup[0])
    clauses_text = [clause.text for clause in sentence_clauses]
    return clauses_text