In one of your reproductions of the results from the paper it would spit out random other names from the dataset. But from your description of the Tom Cruise dataset, there were no other names included. Why didn't you give it the possibility to fail in the same way?

Have to tried replacing "is" with "equals" in the training set where it is valid? I did a search in the article for the word and got no hits.

I'm thinking this might work because "equals" is always logically reversible whereas "is" is not, assuming the statements are technically truthful.