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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def split_text(text, include_part_of_speech=False, strip_english=False, strip_numbers=False):
 u""" Split Chinese text at word boundaries. include_pos: also returns the Part Of Speech for each of the words. Some of the different parts of speech are: r: pronoun v: verb ns: proper noun This all gets returned as a tuple: index 0: the split word index 1: the word's part of speech strip_english: remove all entries that have English or numbers in them (useful sometimes) """


    if not include_part_of_speech:
        seg_list = pseg.cut(text)
        if strip_english:
            seg_list = filter(lambda x: not contains_english(x), seg_list)
        if strip_numbers:
            seg_list = filter(lambda x: not _is_number(x), seg_list)
        return list(map(lambda i: i.word, seg_list))
    else:
        seg_list = pseg.cut(text)
        objs = map(lambda w: (w.word, w.flag), seg_list)
        if strip_english:
            objs = filter(lambda x: not contains_english(x[0]), objs)
        if strip_english:
            objs = filter(lambda x: not _is_number(x[0]), objs)
        return objs

    # if was_traditional:
    #   seg_list = map(tradify, seg_list)

    return list(seg_list)