def METHOD_NAME(
    self, text: str, entities: List[str], nlp_artifacts: NlpArtifacts = None
) -> List[RecognizerResult]:
    """
    Analyze text using Text Analytics.
    :param text: The text for analysis.
    :param entities: Not working properly for this recognizer.
    :param nlp_artifacts: Not used by this recognizer.
    :param language: Text language. Supported languages in MODEL_LANGUAGES
    :return: The list of Presidio RecognizerResult constructed from the recognized
        Flair detections.
    """
    results = []
    sentences = Sentence(text)
    self.model.predict(sentences)
    # If there are no specific list of entities, we will look for all of it.
    if not entities:
        entities = self.supported_entities
    for entity in entities:
        if entity not in self.supported_entities:
            continue
        for ent in sentences.get_spans("ner"):
            if not self.__check_label(
                entity, ent.labels[0].value, self.check_label_groups
            ):
                continue
            textual_explanation = self.DEFAULT_EXPLANATION.format(
                ent.labels[0].value
            )
            explanation = self.build_flair_explanation(
                round(ent.score, 2), textual_explanation
            )
            flair_result = self._convert_to_recognizer_result(ent, explanation)
            results.append(flair_result)
    return results