[LOCKSUIT]

I'll draw a sketch of what your algotithm would look like of that pic in my format...

[LOCKSUIT]

So here we save all the possible pairs linearly up on an angle i mean lol and um, 3 sentences like this, which is, bad, it should be triangles made of triangles like shown before and not every shift over like "and the cat" "the cat ate" "cat me but".

[spydaz]

So here we save all the possible pairs linearly up on an angle i mean lol and um, 3 sentences like this, which is, bad, it should be triangles made of triangles like shown before and not every shift over like "and the cat" "the cat ate" "cat me but".

Answered!

[ranch vermin]

ur ruining his design spyda!!!!

[LOCKSUIT]

lol ranch. Honestly I don't think his program is what I need. That'd be hilariously easy and time saving and powerful if it was.

Again, why does it learn   "word word [word {word] word} word"   (the [ ] or the { }?) over one or the other order? Is it more common/useful? (Either "the lobby at the school" or "lobby at the school was").

It can't store both possible shifts. And when it does store 1, it must re-use it for sentences containing it.

It'll always be quick to point out/see it apart in any sentence (or build using it) ex. "Ya so that girl was at the [lobby at the school] but was tired" and ex. "The hat was at the [lobby at the school] but was missing all week long"

[spydaz]

ur ruining his design spyda!!!!

You cant force good knowledge into a head as the say! -

La-La Land is a real easy place to live -

"I just felt like running! -(Forrest Gump)"

I was explaining a whole strategy... for designing an algorithm...

And how to mould products such a the "Simple Trie Tree"  to your will... but being a non coder he asked so many questions i was up all night ... trying Explain basic Functions / Strategies / Objectives / Rules / Matches .... one of the first level AI ... techniques...

We even discover a super intelligent algorithm process for understanding that data collected needs to be cleaned then categorised before farming information and pre-processed.

its not instant ! there is no solve all and fix all .... you have to Taylor everything to your needs... or your just using peoples projects as "BLOCKS" in your AI process. hoping for a big discovery!

[LOCKSUIT]

Lol I never asked you to explain Ai techniques, I just wanted to know how your program works / if it did what mine requires...

Well obviously I didn't understand what you said then...

[spydaz]

Lol I never asked you to explain Ai techniques, I just wanted to know how your program works / if it did what mine requires...

Well obviously I didn't understand what you said then...

Obviously ; the question was answered; Perhaps your just taking the michael... in future we shall know not to explain anything to you... as the answer was presented but you couldn't take it on board....Perhaps even now you don't get it!....More research for you is required.... we shall keep you to the basics in future!

Pmlamo (peeing myself laughing my ass off) Lol (laughing out loud) <<<<<<<<<<< Breaking it down

Now we know your not serious!

[spydaz]

On expedition now Later guys.... Chat soon!

[LOCKSUIT]

Ok.

Which post is the answer in?

And anyone care to shrink it into a 15 word sentence?

[ivan.moony]

Lock, you have to learn to learn. It can be helpful occasionally, trust me. Sometimes it just pays off to spend an hour or more in learning what other people intended to show you. Often, you can base your own discoveries on what you've learned. There will always be some pointless stuff for you, but generally,  it pays off at the end.

There is some nice stuff out there in outer world. Use it. Expand it, or optimize it. And then ask us to learn from you.

There is no such thing as a self made man.

[LOCKSUIT]

As the thread went along I had read all of his posts.

Ya but ivan, there's 54 posts now...Did any of yous get my desire or his answer? I think we BOTH had a language barrier.

Hopefully yous understand the program/his answer, I need to ask some better questions...

[LOCKSUIT]

Another way to put it simply is I want it to learn by lots of text (or some universal verb/object/predicate structure) that "are is" is BAD and "is soft" is GOOD, i.e. it outputs back out your sentence like this "Another thing   they are      is soft   like cats.".

I have not heard anyone mention/reply back on this subject !

[ivan.moony]

Another way to put it simply is I want it to learn by lots of text (or some universal verb/object/predicate structure) that "are is" is BAD and "is soft" is GOOD, i.e. it outputs back out your sentence like this "Another thing   they are      is soft   like cats.".

I have not heard anyone mention/reply back on this subject !

There are grammarc natural language rules rules that say whether a sentence is well formed. A part of such grammar rules may be written in BNF notation, but if you want a real deal you'll need a link grammar notation. There are a lot of programs that use either a kind of BNF or link grammar to parse texts, but you have to provide them a valid grammar. That grammar could be anything, from grammar for parsing math expressions, over grammars for parsing programming languages, to grammars for parsing natural language sentences.

Some parsers like Stanford Parser come bundeled with a natural language grammar (see references from Don Patrick), but generally, natural language parsing problem stays unsolved problem due to ambiguities that raise by overlapping natural language grammar rules. An example of this is:

Last night I shoot an elephant in my pajamas.

The question here is whether the elephant wears a pajama or the shooter wears pajama. However, there are hints to solve such problems, like `Last night` and `my pajams` parts of the sentence that hint that the shooter wore a pajama, but this is still not a guarantee. Ambiguity resolving could also be done by comparing near sentences from the same paragraph, or by statistical analysis, but it still remains open question in linguistics, which is hoped to be solved when AI would be invented. There are even some contests (like winograd schema challenge) in which competitors (their programs in fact) try to resolve as much ambiguities as they can. I think no one ever made it with 100% correctness. Questions posed in such competitions are like:

A cat didn't enter a box because it was too big. What was big, a cat or a box?

This is a big problem, to answer this question, isn't it? Well, it gives programmers a lots of headaches.

To analyze natural language sentences, some efforts have been made by parsing a sentence corpus by humans, and packaging it in treebanks freely available for download in various versions in various languages. Treebanks could be used as references for checking correct solutions in solving a natural language parsing problem by a machine.

Does this answer your question?

[LOCKSUIT]

Did you hear about Parsey McParseFace? The ambiguity problem is OVER. Human accuracy dude!
https://ai.googleblog.com/2016/05/announcing-syntaxnet-worlds-most.html
give it a test:
https://deepai.org/machine-learning-model/parseymcparseface

I found a link grammer tester looky! Also AbiWord I mayyy have to try it out too then...Now how does it know though!!!!???
http://www.link.cs.cmu.edu/cgi-bin/link/construct-page-4.cgi#submit

Did the programmer dude label each freaking word in English whether it's a noun, verb, etc? That'd take a long time, including how it knows WHICH can fit together....how does it know "I am" "soft like" don't fit together yet "I am" the cat" fit together for a rough example?

If I try AbiWord and it underlines wrong word pairs, this tells me it KNOWS which words can go beside each other.....
https://www.abisource.com/download/
sorry not available anymore wtf you kidding me abiword!!! LOL pft