spacy_demo.py

import spacy.en
from spacy.symbols import VERB, nsubj, dobj

def find_acquisitions(nlp, text, buy_words):
    doc = nlp(text)
    for ent in doc.ents:
        ent.merge(ent.root.tag_, ent.text, ent.label_)
    buy_words = set(nlp.vocab.strings[w] for w in buy_words)
    for token in doc:
        if token.pos == VERB and token.lemma in buy_words:
            buyer = [w for w in token.lefts if w.dep == nsubj]
            bought = [w for w in token.rights if w.dep == dobj]
            if buyer and bought:
                yield token, buyer[0], bought[0]