def METHOD_NAME(self):
    all_ = []
    # e.g. what is the vapour pressure of methane
    selected_p = []
    for triple in self.triples:
        s, p, o = [e.strip() for e in triple.split("\t")]
        if p in self.selected_p:
            if s in iri2labels:
                species_label = random.choice(iri2labels[s])
                # get the label of this species ...
                p_labels = self.selected_p_dict[p]
                p_labels += self.selected_p_labels[p]
                selected_p_label = random.choice(p_labels)
                question = self.normal_question_template % (selected_p_label, species_label)
                row = (question, s, p, o, "normal", species_label, None, None)
                all_.append(row)
    normal_test_set_path = os.path.join(DATA_DIR, "../KGToolbox/CrossGraph", dataset_dir,
                                        "wikidata_numerical_test_set-normal.json")
    print(len(all_))
    with open(normal_test_set_path, "w") as f:
        f.write(json.dumps(all_))
        f.close()
    # df = pd.DataFrame(all_)
    # df.columns = ["question", "head", "rel", "tail", "type", "mention", "operator_type", "numerical_value"]
    # df.to_csv("wikidata_numerical_test_set-normal.tsv", sep="\t")