def extract(self, kg: KG, entities: Entities, verbose: int=0) -> List[List[SWalk]]:
    'Fits the provided sampling strategy and then calls the\n        private _extract method that is implemented for each of the\n        walking strategies.\n\n        Args:\n            kg: The Knowledge Graph.\n            entities: The entities to be extracted from the Knowledge Graph.\n            verbose: The verbosity level.\n                0: does not display anything;\n                1: display of the progress of extraction and training of walks;\n                2: debugging.\n                Defaults to 0.\n\n        Returns:\n            The 2D matrix with its number of rows equal to the number of\n            provided entities; number of column equal to the embedding size.\n\n        '
    self._weisfeiler_lehman(kg)
    return super().extract(kg, entities, verbose)
Fits the provided sampling strategy and then calls the
private _extract method that is implemented for each of the
walking strategies.

Args:
    kg: The Knowledge Graph.
    entities: The entities to be extracted from the Knowledge Graph.
    verbose: The verbosity level.
        0: does not display anything;
        1: display of the progress of extraction and training of walks;
        2: debugging.
        Defaults to 0.

Returns:
    The 2D matrix with its number of rows equal to the number of
    provided entities; number of column equal to the embedding size.
def extract(self, kg: KG, entities: Entities, verbose: int=0) -> List[List[SWalk]]:
    'Fits the provided sampling strategy and then calls the\n        private _extract method that is implemented for each of the\n        walking strategies.\n\n        Args:\n            kg: The Knowledge Graph.\n            entities: The entities to be extracted from the Knowledge Graph.\n            verbose: The verbosity level.\n                0: does not display anything;\n                1: display of the progress of extraction and training of walks;\n                2: debugging.\n                Defaults to 0.\n\n        Returns:\n            The 2D matrix with its number of rows equal to the number of\n            provided entities; number of column equal to the embedding size.\n\n        '
    self._weisfeiler_lehman(kg)
    return super().extract(kg, entities, verbose)