def target_in_utterance_uncapped(bot_utterance, target, USE_model) -> float:
    bot_sentences = re.split(r'[.!?]+', bot_utterance)
    bot_sentences[:] = [x for x in bot_sentences if x]

    best_target_closeness = 0.0
    for bot_sentence in bot_sentences:
        target_closeness = USE_similarity(bot_sentence, target, USE_model)
        if target_closeness > best_target_closeness:
            best_target_closeness = target_closeness

    return best_target_closeness