Question answering is actually much harder than was is presented in the article because most questions people ask are not factoid questions. Consider the following that Watson needed to address at a recent customer engagement (an insurance company):
* Can you help me with life insurance?
* What benefits will I lose when I leave?
* What last minute things should I take advantage of in the military before I go?
The answers to these questions are not entities (people, place, dates) as in factoid questions. They may be procedures, they may depend on the user, further clarification/dialog may be required before being answered, they may not have a single answer or require a combination of answers, etc.
Also Watson does not try to formalize all knowledge even when answering factoid questions. Many of the candidates generated do not actually come from a formal knowledge graph, instead they are generated on the fly from analyzing all the pieces of text that seem contextually relevant.
There isn't that much publicly available information about how Watson works - I'm pretty sure I'd read everything there was in January this year. There might be some more now?
I can't even imagine where to start with "Can you help me with life insurance" - beyond maybe triggering standard sales pitches.
How does Watson decide when to use the knowledge graph and when to look more broadly?
The right way to answer "Can you help me with life insurance" is to start asking the user questions to learn more about their needs - that's one of the way we are currently trying to go beyond the Jeopardy use case.
I'm yet to see a good public implementation of conversational question answering. It's pretty clear Google is headed down that path with Google Now, and I guess Siri is going the same way.
Traditionally question refinement is done using filters and clustering, but of course this focuses the result sets, and is the opposite of what you need in conversational question answering.
* Can you help me with life insurance?
* What benefits will I lose when I leave?
* What last minute things should I take advantage of in the military before I go?
The answers to these questions are not entities (people, place, dates) as in factoid questions. They may be procedures, they may depend on the user, further clarification/dialog may be required before being answered, they may not have a single answer or require a combination of answers, etc.
Also Watson does not try to formalize all knowledge even when answering factoid questions. Many of the candidates generated do not actually come from a formal knowledge graph, instead they are generated on the fly from analyzing all the pieces of text that seem contextually relevant.