def METHOD_NAME(
    self,
    data_path: str,
    dataset_name: str = None,
    provide_pos: bool = False,
    provide_chunk: bool = False,
    provide_doc_ids: bool = False,
    iob: bool = False,
    iobes: bool = False,
    docstart_token: str = None,
):
    self.provide_pos = provide_pos
    self.provide_chunk = provide_chunk
    self.provide_doc_ids = provide_doc_ids
    self.iob = iob
    self.iobes = iobes
    self.docstart_token = docstart_token
    self.num_docs = 0
    self.x_is_tuple = self.provide_pos or self.provide_doc_ids
    data_path = Path(data_path)
    files = list(data_path.glob("*.txt"))
    if "train.txt" not in {file_path.name for file_path in files}:
        if dataset_name == "sentseg_ru":
            url = "http://files.deeppavlov.ai/deeppavlov_data/sentseg_ru_subtitles_data.tar.gz"
        else:
            raise RuntimeError('train.txt not found in "{}"'.format(data_path))
        data_path.mkdir(exist_ok=True, parents=True)
        download_decompress(url, data_path)
        files = list(data_path.glob("*.txt"))
    dataset = {}
    for file_name in files:
        name = file_name.with_suffix("").name
        dataset[name] = self.parse_ner_file(file_name)
    return dataset