How to use the squad.utils.get_phrase function in squad

def ensemble2(context, wordss, y1_list, y2_list):
    start_dict = defaultdict(float)
    stop_dict = defaultdict(float)
    for y1, y2 in zip(y1_list, y2_list):
        span, score = get_best_span(y1, y2)
        start_dict[span[0]] += y1[span[0][0]][span[0][1]]
        stop_dict[span[1]] += y2[span[1][0]][span[1][1]]
    start = max(start_dict.items(), key=lambda pair: pair[1])[0]
    stop = max(stop_dict.items(), key=lambda pair: pair[1])[0]
    best_span = (start, stop)
    return get_phrase(context, wordss, best_span)

def _get2(context, xi, span):
            if len(xi) <= span[0][0]:
                return ""
            if len(xi[span[0][0]]) <= span[1][1]:
                return ""
            return get_phrase(context, xi, span)
        id2answer_dict = {id_: _get2(context, xi, span)

def ensemble3(context, wordss, y1_list, y2_list):
    d = defaultdict(float)
    for y1, y2 in zip(y1_list, y2_list):
        span, score = get_best_span(y1, y2)
        phrase = get_phrase(context, wordss, span)
        d[phrase] += score
    return max(d.items(), key=lambda pair: pair[1])[0]

def ensemble1(context, wordss, y1_list, y2_list):
    """

    :param context: Original context
    :param wordss: tokenized words (nested 2D list)
    :param y1_list: list of start index probs (each element corresponds to probs form single model)
    :param y2_list: list of stop index probs
    :return:
    """
    sum_y1 = combine_y_list(y1_list)
    sum_y2 = combine_y_list(y2_list)
    span, score = get_best_span(sum_y1, sum_y2)
    return get_phrase(context, wordss, span)

def ensemble3(context, wordss, y1_list, y2_list):
    d = defaultdict(float)
    for y1, y2 in zip(y1_list, y2_list):
        span, score = get_best_span(y1, y2)
        phrase = get_phrase(context, wordss, span)
        d[phrase] += score
    return max(d.items(), key=lambda pair: pair[1])[0]

def ensemble2(context, wordss, y1_list, y2_list):
    start_dict = defaultdict(float)
    stop_dict = defaultdict(float)
    for y1, y2 in zip(y1_list, y2_list):
        span, score = get_best_span(y1, y2)
        start_dict[span[0]] += y1[span[0][0]][span[0][1]]
        stop_dict[span[1]] += y2[span[1][0]][span[1][1]]
    start = max(start_dict.items(), key=lambda pair: pair[1])[0]
    stop = max(stop_dict.items(), key=lambda pair: pair[1])[0]
    best_span = (start, stop)
    return get_phrase(context, wordss, best_span)