extract_relations_umls

nlp2 = load_model(MODEL)
nlp2.add_pipe(nlp2.create_pipe("merge_entities"))
nlp2.add_pipe(nlp2.create_pipe("merge_noun_chunks"))

def extract_relations_umls(text, umls):
    ents = {x[0].lower(): x[2] for x in umls}
    rels = []
    for x in nlp2(text):
        if x.dep_ != "ROOT":
            if x.ent_type_ == "ENTITY":
                if x.head.ent_type_ == "ENTITY":
                    rels.append((x.head.lower_, x.dep_, x.lower_))
            else:
                if x.head.ent_type_ == "ENTITY":
                    children = list(x.children)
                    if children and children[0].ent_type_ == "ENTITY":
                        rels.append((x.head.lower_, x.dep_, x.lower_))
                        rels.append((x.lower_, children[0].dep_, children[0].lower_))
    return [(ents.get(x, x), y, ents.get(z, z)) for x, y, z in rels]

rels = extract_relations_umls(text, umls)