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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def update_beliefs(self, corpus_id):
 """Return updated belief scores for a given corpus. Parameters corpus_id : str The ID of the corpus for which beliefs are to be updated. Returns ------- dict A dictionary of belief scores with keys corresponding to Statement UUIDs and values to new belief scores. """

        corpus = self.get_corpus(corpus_id)
        be = BeliefEngine(self.scorer)
        stmts = list(corpus.statements.values())
        be.set_prior_probs(stmts)
        # Here we set beliefs based on actual curation
        for uuid, correct in corpus.curations.items():
            stmt = corpus.statements.get(uuid)
            if stmt is None:
                logger.warning('%s is not in the corpus.' % uuid)
                continue
            stmt.belief = correct
        belief_dict = {st.uuid: st.belief for st in stmts}
        return belief_dict