1. "Who was the 12th president?" - Zachary Taylor 2. "What color wine is cabernet sauvignon?" - Red 3. "Is a ferret a rodent?" - The ferret is the domesticated member of the Order Carnivora, Family Mustelidae and Genus Mustela. A common misconception is that ferrets are rodents.
The real challenge is answering niche questions:
1. What size are the OEM rear wheels of a Honda S2000? 2. How can I fix MySQL error 1064? 3. How do I remove wine from a macbook?
These types of questions aren't answerable by a simple mining of Wikipedia or Encyclopedic knowledge. They represent niches within our society (S2000 owners, programmers, people who spilled wine on their macbooks). Google provides excellent links to pages that contain answers to these questions, but it cannot deduce a single answer or common response. This is why sites like Answers.com, Yahoo! Answers, StackExchange, etc. can flourish, but it's also why an NLP question and answer system is very difficult.
I've been working on a system to mine existing responses to questions - http://gotoanswer.stanford.edu - I only have a small subset of programming-related questions (~10M), but you can get an idea for what I'm trying to do by searching for "How do I remove wine from a macbook?" You'll see that there are results for removing wine the liquid and WINE the windows non-emulator.