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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 dataset(self):
        '''
        Returns the DBContext as a list of interpretations, i.e., a list of
        facts true for each example in the format for TreeLiker.
        '''
        target = self.db.target_table
        db_examples = self.db.rows(target, [self.db.target_att, self.db.pkeys[target]])

        examples = []
        for cls, pk in sorted(db_examples, key=lambda ex: ex[0]):
            facts = self._facts(pk, self.db.pkeys[target], target, visited=set())
            examples.append('%s %s' % (cls, ', '.join(facts)))

        return '\n'.join(examples)