This is based purely on reading the wikipedia entry on Operator grammar, which I find very interesting. I'm hoping someone out there knows enough about this to answer some questions :^)
Wikipedia says that various quantities are "learnable" because they can in principle be determined by data. What is known about whether they are efficiently learnable, e.g. (a) whether a child would acquire enough data to learn the language and (b) whether given the data, learning the language would be computationally feasible? (e.g. polynomial time.) Keep in mind that, you have to learn the language well enough to deal with the fact that you can generate and understand (and thus pretty much have to be able to calculate the likelihood of) a virtually infinite number of sentences never before seen. I presume the answer to these two questions (how much data you need and how easy it is to learn from it) will depend on how you parametrize the various knowledge you learn. So, for example, take a word that takes two arguments. One way to parametrize the likelihood of various arguments would be with a table over all two word combinations, the i,j entry gives the likelihood that the ith word and the jth word are the two arguments. But most likely, in reality, the likelihood of the jth word will be much pinned down conditional on the ith. So one might imagine parametrizing these "learned" coherent selection tables in some powerful way that exposes underlying structure. If you just use lookup tables, I'm guessing learning is computationally trivial, but data requirements are prohibitive. On the other hand, if you posit underlying structure, you can no doubt lower the amount of data required to be able to deal with novel sentences, but I would expect you'd run into the standard problems that finding the optimal structure becomes NP-hard. At this point, a heuristic might or might not suffice, it would be an empirical question. Is there empirical work with this model? Also, I don't see how you can call a model "semantic" when it makes no reference to the world. The model as described by Wikipedia could have the capability of telling me whether a sentence is natural or highly unlikely, but unless I misunderstand something, there is no possibility it could tell me whether a sentence describes a scene. Matt> --- Chuck Esterbrook <[EMAIL PROTECTED]> wrote: >> Any opinions on Operator Grammar vs. Link Grammar? >> >> http://en.wikipedia.org/wiki/Operator_Grammar >> >> http://en.wikipedia.org/wiki/Link_grammar >> >> Link Grammar seems to have spawned practical software, but Operator >> Grammar has some compelling ideas including coherent selection, >> information content and more. Maybe these ideas are too hard or too >> ill-defined to implement? >> >> Or, in other words, why does Link Grammar win the GoogleFight? >> Matt> http://www.googlefight.com/index.php?lang=en_GB&word1=%22link+grammar%22&word2=%22operator+grammar%22 >> (http://tinyurl.com/yvu9xr) Matt> Link grammar has a website and online demo at Matt> http://www.link.cs.cmu.edu/link/submit-sentence-4.html Matt> But as I posted earlier, it gives the same parse for: Matt> - I ate pizza with pepperoni. - I ate pizza with a friend. - I Matt> ate pizza with a fork. Matt> which shows that you can't separate syntax and semantics. Many Matt> grammars have this problem. Matt> Operator grammar seems to me to be a lot closer to the way Matt> natural language actually works. It includes semantics. The Matt> basic constraints (dependency, likelihood, and reduction) are Matt> all learnable. It might have gotten less attention because its Matt> main proponent, Zellig Harris, died in 1992, just before it Matt> became feasible to test the grammar in computational models Matt> (e.g. perplexity or text compression). Also, none of his Matt> publications are online, but you can find reviews of his books Matt> at http://www.dmi.columbia.edu/zellig/ Matt> -- Matt Mahoney, [EMAIL PROTECTED] Matt> ----- This list is sponsored by AGIRI: Matt> http://www.agiri.org/email To unsubscribe or change your Matt> options, please go to: Matt> http://v2.listbox.com/member/?& ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=e9e40a7e