Steve, So you are defining a numerical system (like a vector system) using the most significant semantic units? I could see how that (or some other numerical system that used a finite number of defined semantic units) might be very effective doing some kind of fundamental parsing. I don't think any systems like this would be very useful for general AGI because I think the system would have to be capable of learning millions of sub-cases, like how particular people use words in various circumstances.
Are you talking about something like that? Jim Bromer On Mon, Mar 25, 2013 at 12:57 PM, Jim Bromer <[email protected]> wrote: > On Fri, Mar 22, 2013 at 6:16 PM, Steve Richfield < > [email protected]> wrote: > >> PM, >> Reading these, I can see that: >> 1. Working with ordinals would speed this process up by more than an >> order of magnitude in performing *exactly* the same analysis, over >> working with character strings... >> > > Could you explain this kind of remark to me. I haven't been able to > figure out a way to make any kind of numeric method work well over the > general kinds of relations that you'd expect to encounter in AGI. If all > systems had a direct correspondence to a dimensional system then you could > get some traction out of these things. Or, if general reasoning did not > need to rely both on intersections and simple arithmetic (or simple logic) > then numeric methods would be extremely efficient. > > Jim Bromer > > > > On Fri, Mar 22, 2013 at 6:16 PM, Steve Richfield < > [email protected]> wrote: > >> PM, >> >> Reading these, I can see that: >> >> 1. Working with ordinals would speed this process up by more than an >> order of magnitude in performing *exactly* the same analysis, over >> working with character strings, e.g. in LISP. >> >> 2. The first book describes a system that finds itself "in the weeds" >> with the first syntactical break in a sentence, where it "jumps to >> confusions" by presuming the next word to be the beginning of a new >> sentence (when more likely a presumed noun was missing), an issue that the >> second book apparently seeks to address. >> >> 3. In dealing with the ontological and other subtle issues, the method >> described in the 2nd book will have to make the SAME tests that any other >> system would have to make to see if particular semantic structures are >> present. What good is it to avoid semantic structures, only to have to >> later analyze them? >> >> Note that WolframAlpha.com and DrEliza.com don't even bother "parsing" in >> the same sense as Hausser uses the term, and instead only work with >> identifiable semantic units. These applications have little use for such >> information. I have looked at what the big costs are in DrEliza.com from >> the lack of full parsing. The primary problem is that it is now blind to >> whether someone is describing their own problems, or someone else's >> problems. Also, when negation meets compound and complex sentence >> structure, the logic in DrEliza.com would more likely misunderstand it than >> get it right, and so I have disabled acting on such sentences. >> >> Note that improper multiple negation is SO common in everyday English >> that correct parsing is as likely as not to arrive at the wrong meaning. >> >> I think the "break" in this discussion is that almost everyone's ultimate >> goal is to identify the semantics, whereas this method identifies the >> syntax. A presumption has been made that parsing syntax is a necessary step >> on the way to recognizing semantics, which is clearly made here in >> rejecting the analysis of semantic structures. Unfortunately, semantics is >> EXACTLY what most applications need from a parser, so this "hole" must then >> be filled in later in the analysis, and filling this hole in will slow this >> approach down, exactly as it slows other approaches down. >> >> It is ALWAYS faster to skip the hard stuff, which is really great if you >> don't need it. I can see Hausser's approach working as part of a language >> translator, ESPECIALLY for scientific material like the Russian Academy of >> Sciences is now working on, where the translation wants to AVOID semantic >> analysis as much as possible. A computer can potentially only "understand" >> things that are already known, whereas the entire object of scientific >> papers is to explore the *UN*known. >> >> On a side note - note the copious spelling errors. There couldn't have >> been much review of this material. If the author can't even get his friends >> to read his writings... >> >> Did I miss anything? >> >> Steve >> ================= > > ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
