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Greg Thole

How Is Wolfram|Alpha Like a Matryoshka Doll?

June 12, 2012 —
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Wolfram|Alpha is different from most of the tools out there on the web that you might use to get answers. Rather than inundate you with lists of links to web pages that may or may not be useful, Wolfram|Alpha works to understand your query.

What really sets these different approaches apart is how they deal with complexity in queries. Whether there are many concurrent factors to your question or you have a unique math computation with an answer that simply does not exist on some web page, Wolfram|Alpha is your best bet for a web service that actually understands what you are asking.

One of the ways that complexity can appear in queries is in depth, when there are multiple steps to a question. To understand what we mean by “depth,” think of the beautiful Matryoshka dolls that all fit inside of each other.

To answer a query like “elevation of Steven Spielberg’s birthplace“, the first step is to recognize that “Steven Spielberg” and “birthplace” can be combined to form a location.

(elevation) of ((Steven Spielberg’s) (birthplace))

We can then combine that location with the “elevation” and form a nested statement, and now we’re off to the races:

elevation of Steven Spielberg's birthplace

These kinds of questions can be quite natural:

And Wolfram|Alpha can handle multiple layers of this kind of nesting:

angle relations of the crystal system of the symmetry group of a tetrahedron

This sort of thing can quickly begin to feel contrived. But that’s OK, and if it makes you feel better, you can add a little more structure to help see the relationships in the input, such as in this query: “angle relations (crystal system (symmetry group of a tetrahedron))

But what happens if the inner combination is not a single thing, but rather multiple things? Wolfram|Alpha still knows what to do:

Pretty cool, right?

There is still plenty to do in this realm. We’re ensuring that the links between our datasets all conform to the standards required for this kind of nesting; building up the natural-language capacity to handle qualifiers (such as dates for nested population queries); and, of course, continuously extending the relational patterns that Wolfram|Alpha can recognize. And so we remain hard at work building up the computable capacity of the world’s only real knowledge engine.


1. You say that the main differrence with Wolfram Alpha is that it works to umderstand the query. Another major differrence is that its data is more reliable because it goes through a checking process called ‘curation’ to qualify for inclusion in its database.

2.Please add here Wolfram Apha’s preferred form of input for nested queries in a form that is usable for input. At present you show blocks but we can’t input blocks. I use brackets but cannot be sure this is right for Wolfram Alpha.

Posted by Brian Gilbert June 15, 2012 at 5:27 am

Oops, I see you have used brackets in an example. It would help if you showed how having resolved the query/queries within single brackets the nested
lquery became simpler the process being repeated until a simple query remained with no brackets at all.
I am assuming WA uses unique tags to its database and gives them IDs. I will show these as WATAGn. I assume that each Mathematica function also has a unique ID.

Step 1
(elevation) of ((Steven Spielberg’s) (birthplace))
Step 3.


Step 4
22 feet

Posted by Brian Gilbert June 15, 2012 at 5:56 am

Strangely, yesterday I responed to a question on the Forum about muliti dimensional space. This until now I would have dismissed it as having no significance to me. Yet now I can see all knowledge existing in a multidimensional space and the query narrowing it down to the space/s where the answer exists.

Posted by Brian Gilbert June 15, 2012 at 6:03 am

It would be very useful if W|A would go to Mathematica direction, when one can ask a series of queries: W|A answer is used to enter another query. That is a real Matreshka.

Posted by RNVSU July 29, 2012 at 5:37 pm