August 31, 2007

Parsing Miss South Carolina's Statement

It’s not like it’s easy to parse Wikipedia, but at least most of the its text is (usually) written with correct spelling, capitalized proper names, meaningful paragraph structure and so on. A natural question is: how will our system perform on the rest of the Web with all of its slang, non-standard syntax, and so on? To put Powerset to the test, two of our engineers, Lukas Biewald and Brendan O'Connor, ran our entire parsing and indexing system on the hardest corpus we could find: Miss South Carlolina's response to the question, "Recent polls have shown that a fifth of Americans can't locate the US on a map. Why do you think this is?"

They fed this transcription into the XLE verbatim, disfluencies and all:

I personally believe that U.S. Americans are unable to do so because uh some uh people out there in our nation don't have maps and uh I believe that our ed- education like such as in South Africa and uh the- the Iraq everywhere like such as and I believe that they should uh our education over here in the U.S. should help the U.S. or- or- should help South Africa and should help the Iraq and the Asian countries so we will be able to build up our future
One might think that such a convoluted mess of words (I hesitate to call it "English") would be impossible to parse, but here is the C-structures that our parser generates: Parse

Unsurprisingly, the sentence is fragmented quite a bit, but the parser clearly managed to extract useful structure throughout the sentence. The last large verb phrase “should help South Africa and should help the Iraq and the Asian countries so we will be able to build up our future” seems very close to correct, which is pretty impressive (Language Log has more discussion on the weird “the Iraq” construction). The output of the semantics system is too long to put here, but in some ways, it’s amazing that we were able to extract any semantics at all.

And, believe it or not, we can actually run some queries against the Carolina Index (as it's known at Powerset). It's hard to think of a reasonable question, but we asked, "Who does education help?" and returned and highlighted the right answer: "Americans". Or should we have returned "U.S. Americans"?

Who does education help

Comments (29)

I am a little surprised that the system does not return the U.S. from the phrase “our education over here in the U.S. should help the U.S.” instead of Americans, assuming that semantics at the phrase level / sentence level is being used along with additional lexico-syntactic features etc.. The word/entity “Americans” highlighted seems to be somewhat dislodged with respect to the query context unless some sort of discourse analysis is als taken into account.

I am a little surprised that the system does not return the U.S. from the phrase “our education over here in the U.S. should help the U.S.” instead of Americans, assuming that semantics at the phrase level / sentence level is being used along with additional lexico-syntactic features etc.. The word/entity “Americans” highlighted seems to be somewhat dislodged with respect to the query context unless some sort of discourse analysis is als taken into account. But if it doing that, and is not merely due to chance based on some statistical model, then thats pretty impressive.

So if this is what the parse tree for something as horrible as Miss South Carlolina’s response, what does the tree look like for a properly structured paragraph?

Hilarious. Absolutely amazing. I bet Ms. SC wishes that everyone in the audience was as fluent as Powerset.

Keep feeding this crapola into Powerset and it’ll start thinking “uh” is an important word…

This was a very smart idea by powerset. Kudos on the original thinking behind parsing Miss South Carolina’s statement.

http://www.youtube.com/watch?v=ccYoVnBc_fk&mode=related&search= YouTube - George Carlin: education and the owners of America

Two of our students ran the answer through UMBC’s Ontosem text understanding system. See the results here…

http://ebiquity.umbc.edu/blogger/2007/09/05/parsing-blond-speak/

Powerset technology is far from being the state of the art, but their P.R are defiantly do.

Powerset technology is far from being the state of the art, but their P.R are definitely do.

By the when are you guys launching the private beta… I signed up for it and waiting to see…

I wonder what a search request from the beauty contestant would do to your search engine.. One thing that would be indespensable is to provide a phrase that shows what the search engine understood.. like the google’s “did you mean this?”. Often they are right.

Interested to know what kind of processing power your robots will have? If it takes 10 years to get thru the net, might be out of date before it is done.

Ruthless QA. Very good.

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Well, it looks like Miss south carolina’s word of wisdom have started to spread over the WWW. Even great philosophers now recognize the rightness of her views and the accuracy of her thoughts:

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Too bad for all this spam on the board. But this is quite funny!

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