def get_self_check_nli(output, sampled_passages):
    # spacy sentence tokenization
    sentences = [sent.text.strip() for sent in nlp(output).sents] 
    selfcheck_nli = SelfCheckNLI(device=mps_device) # set device to 'cuda' if GPU is available
    sent_scores_nli = selfcheck_nli.predict(
        sentences = sentences, # list of sentences
        sampled_passages = sampled_passages, # list of sampled passages
    )
    df = pd.DataFrame({
    'Sentence Number': range(1, len(sent_scores_nli) + 1),
    'Probability of Contradiction': sent_scores_nli
    })
    return df