def METHOD_NAME(clean_duplication_ui: UserInterface) -> None:
    clean_duplication_ui._clustering_method_drop.value = "ngram-fingerprint"
    clusters = clean_duplication_ui._clusterer.get_page(0, 5)
    clusters_check = pd.Series(
        [
            [("Québec", 3), ("Quebec", 2), ("quebec", 1)],
            [("Vancouver", 3), ("vancouver", 2)],
        ],
        name="city",
    )
    # set the ngram size to 1
    clean_duplication_ui._ngram_text.value = "1"
    clusters2 = clean_duplication_ui._clusterer.get_page(0, 5)
    # check for either ordering of clusters, since they're
    # only sorted by the length of the cluster the order isn't
    # guaranteed
    clusters_check2 = pd.Series(
        [
            [("Québec", 3), ("Quebec", 2), ("quebec", 1)],
            [("Vancouver", 3), ("vancouver", 2), ("vancouverr", 1)],
            [("Ottowa", 2), ("otowa", 1)],
        ],
        name="city",
    )
    clusters_check3 = pd.Series(
        [
            [("Vancouver", 3), ("vancouver", 2), ("vancouverr", 1)],
            [("Québec", 3), ("Quebec", 2), ("quebec", 1)],
            [("Ottowa", 2), ("otowa", 1)],
        ],
        name="city",
    )
    assert clusters_check.equals(clusters)
    assert clusters_check2.equals(clusters2) or clusters_check3.equals(clusters2)