def METHOD_NAME(split):
    """Generates training data for training dpr
    """
    data = json.load(open("data/ottqa/released_data/"+split+".json"))
    question_table_id_dict = {}
    all_table_ids = list(load_all_tables().keys())
    neg_tables= all_table_ids.copy()
    not_found = []
    for d in tqdm(data):
        question = d['question']
        pos_table_id = d['table_id']
        if pos_table_id not in all_table_ids:
            not_found.append(pos_table_id)
            continue
        else:
            neg_tables.remove(pos_table_id)
        neg_table_id = random.choice(neg_tables)
        question_table_id_dict[question] = {"pos_table":pos_table_id,"neg_table":neg_table_id}
        neg_tables.append(pos_table_id)
    json.dump(question_table_id_dict,open("data/ottqa/triples_dict_"+split+".json","w"))