So that indicates that the natural language parsing isn't super advanced.
"Traditional"-style dependency parsing should be able to solve that, and some of the Facebook AI group's recent work indicates that neural-network based parsing should be able to handle it too.
My toy QA system can handle the second case, without even doing dependency parsing.
It's not clear to me if this is a problem or not. If their voice recognition is as good as it seems that's pretty significant technology.
For example, we haven't done movie show times yet either. Doesn't mean the natural language parsing isn't advanced ;)
"How is the weather tomorrow?" "How about Saturday?" "And Sunday?" That line of questioning worked surprisingly well.
Who is Bill Clinton's daughter's husband's daughter?
Who is Bill Clintron's daughter's husband's daughter's grandfather?
Who is Bill Clinton's house?
Siri passes every single question, verbatim, to WolframAlpha and it gets none of them right.
[2] is a good architectural overview.
For limited domain knowledge base building, DeepDive[3] is state-of-the-art. They don't have a QA interface though.
[1] https://github.com/TScottJ/OpenEphyra
[2] https://mu.lti.cs.cmu.edu/trac/Ephyra/wiki/Docs/Architecture...
Having tried it somewhat extensively I'm quite disappointed - I don't mean to say it's bad but that video was definitely curated in terms of questions.
The voice understanding is impressive, but obviously a video can show the best-case.
The factual questions themselves aren't hard. I've written a toy QA system, and it could handle the base case of those - they are just straight querying on Freebase/DBpedia.
The longer question ("the population, land area and capitals of Japan, India and China") was good.
If anyone has a working copy, I'd like to know which of these it can handle:
"Who is Bill Clinton?"
"Who is Bill Clinton's daughter?"
"Who did Bill Clinton's daughter marry?"
If it can get the third level then it's pretty good. From memory something like OpenEphyra can sometimes get that 3rd level, but usually fails.
I thought the contextual querying (where one query led to another and it had to remember the previous details) was pretty good.