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Comment Re:Not entirely helpful (Score 2, Informative) 138

Semantic processing systems like this (it's not something new) aren't usually able to determine correctness. The truth of a statement is assumed and the best these NLP engines can do at the moment is identify conflicts and maybe use some reputation metrics to assign a veracity rating to a particular statement, or notify the user that there are differing conclusions. These systems are just really, like the summary states, "information extraction" systems. Just as a regular search engine will return you the results from the data set, that's what these types of semantic extraction engines usually do, except the data is processed in a semantically-organized way so that you can query with semantics/natural language constraints instead of just keywords and boolean constraints.

There are some that incorporate some intention or opinion polarity detection, but even those are not capable to sorting "truth" versus "conspiracy".

Additionally, semantic extraction output, like named entities and semantic relations, are useful for many other applications.

Comment Re:Leap Forward? (Score 1) 213

I don't think current QA systems would be confused by that question, actually. In the simplest case of just keyword searching for the appropriate passage, the occurence of "author" with a type of town called "hamlet" will be far smaller than "author" with the play name "Hamlet". Not to mention some systems will pre-mark "Hamlet" as some category precluding a town (like "play"). This lack of co-occurrence also assists statistical methods when learning.

The rhyming and puns will be the more difficult tasks to handle.

Comment Not that immediately novel (Score 1) 213

Parsing of the questions is the really difficult part of QA. However, the usage of category names isn't something brand new in the field. See the NIST TREC Question Answering competition. The last couple of years' challenges involved a group of questions referencing a "target" and/or the previous question or previous answer to correctly formulate the current answer.

Example:
TARGET: John William King convicted of murder
Q1: How many non-white members of the jury were there?
Q3: Where was the trial held?
Q4: When was King convicted?
Q5: Who was the victim of the murder?

Comment Re:Somehow I doubt it (Score 1) 422

Sorry, wrong stage. From stage 1: "To keep the dynamic pressure on the vehicle below a specified level, on the order of 580 pounds per square foot (max q), the main engines are throttled down at approximately 26 seconds and throttled back up at approximately 60 seconds."

http://spaceflight.nasa.gov/shuttle/reference/shutref/events/1stage/

Comment Re:Somehow I doubt it (Score 1) 422

don't they have to power down a little as they break the sound barrier?

"The main engines are throttled down at approximately seven minutes 40 seconds into the mission to maintain 3 g's for physiological and structural constraints." Space Shuttle ref manual: http://spaceflight.nasa.gov/shuttle/reference/shutref/events/2stage/

Comment When competing directly with cell phones? (Score 1) 318

At what point do these stripped-down netbooks begin competing directly with large screen, wi-fi/wan-enabled cell phones that can be used as a 'browser in a box' with office document reading/editing, games, email, IM, plus being a cell phone?

Reaching the levels of $200 and below are right at subsidized smartphone levels. With new chips like Qualcomm's 1Ghz snapdragon now in use in a phone with a 4.1", 480x800 touchscreen, what makes a netbook at these levels competitive? Would screen size alone win out over features?

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