def jaccard_sim_filtering(sentences_df, sentece_col="sentence", threshold=0.8):
    """
    Function used to filter sentences by Jaccard similarity

    ---

    **Arguments**\n
    `sentences_df` (DataFrame): DataFrame with sentences and which contains *sentence* column. \n
    `sentence_col` (String): Name of the sentence column in data frame. Default value = "sentence".\n
    `threshold` (float): Jaccard similarity score threshold used for filtering. Default value = 0.8.

    ---

    **Returns**\n
    `sentences_df` (DataFrame): DataFrame filtered by Jaccard similarity.
    """

    sentence_set_list = sentences_df[sentece_col].str.split(' ').apply(lambda x: set(x)).values
    for i in range(0, len(sentence_set_list), 1):
        for j in range(i + 1, len(sentence_set_list), 1):
            a = sentence_set_list[i]
            b = sentence_set_list[j]
            c = a.intersection(b)
            sim_score = float(len(c)) / (len(a) + len(b) - len(c))
            if sim_score > threshold:
                sentences_df.loc[i, sentece_col] = 'FILTERED'
                break
    return sentences_df[~(sentences_df[sentece_col] == 'FILTERED')].reset_index(drop=True)