def METHOD_NAME(self,table_passage_row,answer_text,st_out_text):
    sentences = []
    all_sentences = sent_tokenize(table_passage_row)
    for s in all_sentences:
        if answer_text.lower() in s.lower():
            sentences.append(s)
    # adding sentences filtered using sentence-transformer similarity measure.
    sentences.extend(sent_tokenize(st_out_text))
    # permuting sentences.
    sentences = np.random.permutation(sentences)
    sentences = ' '.join(sentences)
    return sentences