def METHOD_NAME(self, *, predictions=None, references=None, **kwargs) -> Dict[str, Any]:
    if not predictions:
        raise ValueError("No predictions provided")
    elif not references:
        raise ValueError("No references provided")
    predictions = dict(map(self._convert_pred_to_entry, predictions))
    references = dict(map(self._convert_ref_to_entry, references))
    # TODO: parameterize
    skip_missing_example_ids = False
    long_non_null_threshold = 2
    short_non_null_threshold = 2
    long_answer_stats, short_answer_stats = score_answers(
        gold_annotation_dict=references, pred_dict=predictions,
        skip_missing_example_ids=skip_missing_example_ids,
        long_non_null_threshold=long_non_null_threshold,
        short_non_null_threshold=short_non_null_threshold)
    metrics = pretty_print(long_answer_stats=long_answer_stats, short_answer_stats=short_answer_stats)
    return metrics