I copy the code from this repo: https://github.com/iamrkg31/sentence-to-clauses

parse.py

import re

import nltk


def get_verb_phrases(t):
    verb_phrases = []
    num_children = len(t)
    num_VP = sum(1 if t[i].label() == "VP" else 0 for i in range(0, num_children))

    if t.label() != "VP":
        for i in range(0, num_children):
            if t[i].height() > 2:
                verb_phrases.extend(get_verb_phrases(t[i]))
    elif t.label() == "VP" and num_VP > 1:
        for i in range(0, num_children):
            if t[i].label() == "VP":
                if t[i].height() > 2:
                    verb_phrases.extend(get_verb_phrases(t[i]))
    else:
        verb_phrases.append(' '.join(t.leaves()))

    return verb_phrases


def get_pos(t):
    vp_pos = []
    sub_conj_pos = []
    num_children = len(t)
    children = [t[i].label() for i in range(0, num_children)]

    flag = re.search(r"(S|SBAR|SBARQ|SINV|SQ)", ' '.join(children))

    if "VP" in children and not flag:
        for i in range(0, num_children):
            if t[i].label() == "VP":
                vp_pos.append(t[i].treeposition())
    elif not "VP" in children and not flag:
        for i in range(0, num_children):
            if t[i].height() > 2:
                temp1, temp2 = get_pos(t[i])
                vp_pos.extend(temp1)
                sub_conj_pos.extend(temp2)
    # comment this "else" part, if want to include subordinating conjunctions
    else:
        for i in range(0, num_children):
            if t[i].label() in ["S", "SBAR", "SBARQ", "SINV", "SQ"]:
                temp1, temp2 = get_pos(t[i])
                vp_pos.extend(temp1)
                sub_conj_pos.extend(temp2)
            else:
                sub_conj_pos.append(t[i].treeposition())

    return (vp_pos, sub_conj_pos)


def print_clauses(parse_str):
    sent_tree = nltk.tree.ParentedTree.fromstring(parse_str)
    clause_level_list = ["S", "SBAR", "SBARQ", "SINV", "SQ"]
    clause_list = []
    sub_trees = []
    # sent_tree.pretty_print()

    # break the tree into subtrees of clauses using
    # clause levels "S","SBAR","SBARQ","SINV","SQ"
    for sub_tree in reversed(list(sent_tree.subtrees())):
        if sub_tree.label() in clause_level_list:
            if sub_tree.parent().label() in clause_level_list:
                continue

            if (len(sub_tree) == 1 and sub_tree.label() == "S" and sub_tree[0].label() == "VP"
                    and not sub_tree.parent().label() in clause_level_list):
                continue

            sub_trees.append(sub_tree)
            del sent_tree[sub_tree.treeposition()]

    # for each clause level subtree, extract relevant simple sentence
    for t in sub_trees:
        # get verb phrases from the new modified tree
        verb_phrases = get_verb_phrases(t)

        # get tree without verb phrases (mainly subject)
        # remove subordinating conjunctions
        vp_pos, sub_conj_pos = get_pos(t)
        for i in reversed(vp_pos):
            del t[i]
        for i in reversed(sub_conj_pos):
            del t[i]

        subject_phrase = ' '.join(t.leaves())

        # update the clause_list
        for i in verb_phrases:
            clause_list.append(subject_phrase + " " + i)

    print(clause_list)
    return clause_list