Artificial Intelligence

After WikiCorpus and some NL algorithms for machine reading/writing, I'm thinking of moving towards language understanding (NLU) post-processing for sentences like:

“Once the characteristic numbers of most notions are determined, the human race will have a new kind of tool, a tool that will increase the power of the mind much more than optical lenses helped our eyes, a tool that will be as far superior to microscopes or telescopes as reason is to vision.”

— Leibniz

This sentence compares a described tool to microscopes and telescopes, reason to vision, and compares those two comparisons. So, after an initial semantic parsing, a rule system may permute the structured knowledge into a format more conducive to machine reasoning and NLU.

However, this is moving from NL towards artificial intelligence or, at least, machines that can demonstrate intelligent behavior.

user> Birds are to air as fish are to what?
machine> Water.
user> Why?
machine> Birds move through the air and fish move through water.

Or,

user> Telescopes are to vision as what is to reasoning?
machine> A new kind of tool that the human race will have after the characteristic numbers of most notions are determined, according to Leibniz.

This sort of NL interaction appears to require machine reading, kb search, paraphrase generation, kb search and machine writing. A goal of mine after processing text into a knowledge representation is an NL interface (requiring machine reading/writing) to demonstrate NLU. The algorithm for the above examples is tentatively all-paths discovery, path permuting and parallel search of the kb.

Pseudocode:

// n1 is to n2 as n3 is to what?
// n1 is to n2 as what is to n4?
Nodes[] IsToAsIsTo(n1,n2,n3,n4)
{
 Paths[] P = FindAllPaths(n1,n2);
 Paths[] PP = Rephrases(P);
 Nodes[] N = null;
 if( n4 == null ) N = Search(n3,PP);
 else if( n3 == null ) N = Search(PP,n4);
 return N;
}