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Comment by nl | Hacker News Reader

What is it that impresses people here?

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.

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The first question returns Wikipedia info, the second two just say "Showing search results for: ...".

Thanks.

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.

Soundhound programmer here: We just haven't developed that domain of knowledge yet. The natural language part of things can absolutely understand that, but the underlying base of understanding hasn't been developed.

For example, we haven't done movie show times yet either. Doesn't mean the natural language parsing isn't advanced ;)

It seems like you've turned some things off. One if the demo videos had a question like "What is the population if the capitol of the main that has the Space Needle?" When I tried that question tonight, it returned a Wikipedia link for Washington DC and second answer was strangely Pyongyang. Asking directly about the population of Washington DC, it gave that answer. Who is the President of the United States, returned a Wikipedia article about the (office of the) POTUS. I intended to follow that question with "How tall is he?" -- a question Google demonstrated at Google I/O 3 years ago.

"How is the weather tomorrow?" "How about Saturday?" "And Sunday?" That line of questioning worked surprisingly well.

I can tell you what's so impressive: 1.) It does not just answer isolated questions but it has a reprentation of the discourse. You see that when guy in the video follows up on a previous query related to mortgages. 2.) It is incremental, that means it starts processing the input while you are still talking. That's what allows it to be so fast. In principle, that allows it also to interrupt your sentence and ask for clarification. 3.) It has good understanding of complex topics and that allows it to ask clarification questions and additional details needed to answer a question.

Who is Bill Clinton's daughter's husband?

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?

Just tested it. It fails all of the above and just returns a websearch.

Google Now does surprisingly well on all but the third question, though if you ask "Who is Chelsey Clinton's husband's father" it gets the right answer.

Siri passes every single question, verbatim, to WolframAlpha and it gets none of them right.

@nl noob here. I'd like to try building a toy QA systems (but in limited domain. For example, wild life). Can you please provide some open source pointers ? Is OpenEphyra the one I should look into ? Thanks!

Maybe a good idea to study this then, could be useful to help drive your understanding on the problem domain.

http://sirius.clarity-lab.org

OK. Thanks. Aside, looked into the sirius video and I kept craving for a demo :)

The GitHub version of OpenEphyra[1] is a good place to start. From memory you need to much around some to get the Bing-based knowledge-miner to work, but it is pretty good once you do.

[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...

[3] http://deepdive.stanford.edu/

I would like to know if you can ask the following group of questions : - "What is Bill Clinton's age ?" - "Who did he marry ?"

ok so I have an invite and it fails all questions except "Who is Bill Clinton"

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.

Google Now gets one and two and flunks the third. Interesting test.

Regular Google search get's them all correct.

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