def METHOD_NAME(
    specification_file_path: FilePathType,
    data_folder_path: Optional[FolderPathType] = None,
    output_folder_path: Optional[FolderPathType] = None,
    overwrite: bool = False,
):
    """
    Run conversion to NWB given a yaml specification file.
    Parameters
    ----------
    specification_file_path : FilePathType
        File path leading to .yml specification file for NWB conversion.
    data_folder_path : FolderPathType, optional
        Folder path leading to root location of the data files.
        The default is the parent directory of the specification_file_path.
    output_folder_path : FolderPathType, optional
        Folder path leading to the desired output location of the .nwb files.
        The default is the parent directory of the specification_file_path.
    overwrite : bool, default: False
        If True, replaces any existing NWBFile at the nwbfile_path location, if save_to_file is True.
        If False, appends the existing NWBFile at the nwbfile_path location, if save_to_file is True.
    """
    if data_folder_path is None:
        data_folder_path = Path(specification_file_path).parent
    if output_folder_path is None:
        output_folder_path = Path(specification_file_path).parent
    else:
        output_folder_path = Path(output_folder_path)
    specification = load_dict_from_file(file_path=specification_file_path)
    schema_folder = Path(__file__).parent.parent.parent / "schemas"
    specification_schema = load_dict_from_file(file_path=schema_folder / "yaml_conversion_specification_schema.json")
    sys_uri_base = "file:/" if sys.platform.startswith("win32") else "file://"
    validate(
        instance=specification,
        schema=specification_schema,
        resolver=RefResolver(base_uri=sys_uri_base + str(schema_folder) + "/", referrer=specification_schema),
    )
    global_metadata = specification.get("metadata", dict())
    global_conversion_options = specification.get("conversion_options", dict())
    data_interfaces_spec = specification.get("data_interfaces")
    data_interfaces_module = import_module(name=".datainterfaces", package="neuroconv")
    data_interface_classes = {key: getattr(data_interfaces_module, name) for key, name in data_interfaces_spec.items()}
    CustomNWBConverter = type(
        "CustomNWBConverter", (NWBConverter,), dict(data_interface_classes=data_interface_classes)
    )
    file_counter = 0
    for experiment in specification["experiments"].values():
        experiment_metadata = experiment.get("metadata", dict())
        for session in experiment["sessions"]:
            file_counter += 1
            source_data = session["source_data"]
            for interface_name, interface_source_data in session["source_data"].items():
                for key, value in interface_source_data.items():
                    if key == "file_paths":
                        source_data[interface_name].update({key: [str(Path(data_folder_path) / x) for x in value]})
                    elif key in ("file_path", "folder_path"):
                        source_data[interface_name].update({key: str(Path(data_folder_path) / value)})
            converter = CustomNWBConverter(source_data=source_data)
            metadata = converter.get_metadata()
            for metadata_source in [global_metadata, experiment_metadata, session.get("metadata", dict())]:
                metadata = dict_deep_update(metadata, metadata_source)
            nwbfile_name = session.get("nwbfile_name", f"temp_nwbfile_name_{file_counter}").strip(".nwb")
            session_conversion_options = session.get("conversion_options", dict())
            conversion_options = dict()
            for key in converter.data_interface_objects:
                conversion_options[key] = dict(session_conversion_options.get(key, dict()), **global_conversion_options)
            converter.run_conversion(
                nwbfile_path=output_folder_path / f"{nwbfile_name}.nwb",
                metadata=metadata,
                overwrite=overwrite,
                conversion_options=conversion_options,
            )
    # To properly mimic a true dandi organization, the full directory must be populated with NWBFiles.
    all_nwbfile_paths = [nwbfile_path for nwbfile_path in output_folder_path.iterdir() if nwbfile_path.suffix == ".nwb"]
    if any(["temp_nwbfile_name_" in nwbfile_path.stem for nwbfile_path in all_nwbfile_paths]):
        dandi_metadata_list = []
        for nwbfile_path in all_nwbfile_paths:
            dandi_metadata = _get_pynwb_metadata(path=nwbfile_path)
            dandi_metadata.update(path=nwbfile_path)
            dandi_metadata_list.append(dandi_metadata)
        named_dandi_metadata_list = create_unique_filenames_from_metadata(metadata=dandi_metadata_list)
        for named_dandi_metadata in named_dandi_metadata_list:
            if "temp_nwbfile_name_" in named_dandi_metadata["path"].stem:
                dandi_filename = named_dandi_metadata["dandi_filename"].replace(" ", "_")
                assert (
                    dandi_filename != ".nwb"
                ), f"Not enough metadata available to assign name to {str(named_dandi_metadata['path'])}!"
                named_dandi_metadata["path"].rename(str(output_folder_path / dandi_filename))