There's still a rule here though, and one that can be learnt: when someone references an object when asked about a person, the inference is the object has something to do with the person. It doesn't directly answer the question, but is a clue that can be used to predict the answer.
Yeah, it doesn't seem all that hard to form up an association between the car mentioned and Curly. From that association and the association between the car and the parking lot (space/time locality) -- it seems reasonable to add some probability to an association between "Curly" and "here/now" - and from there be able to answer some questions about Curly (Does Curly have a car? Which car? Is Curly back from vacation?) -- all from pretty straight forward parsing based on nouns and proximity.
Not saying that parsing natural language is easy, just not sure this is such a terribly hard example (for a system that's prepared to cheat and/or appear stupid/gullible).
Eg, parse both the above and the below correctly with the same parser:
Ann: Have you seen my dragon?
Dad: I think he is playing with the bear in your room.
Ann: Ok.
(Personally I'd be happy if a system thought Ann had a dragon, but CIA analysts might be less than enthusiastic)
