Re: [agi] Parsing theories
On 5/23/07, Mark Waser <[EMAIL PROTECTED]> wrote: systems in that there has been success in processing huge amounts (corpuses, corpi? :-) of data and producing results -- but it's *clearly* not the way corpora - 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
Re: [agi] Parsing theories
> As I think about it, one problem is, depending on how its > parametrized, its not going to build much of a world model. > Say for example it uses trigrams. The average hs grad knows > something like 50,000 words. So there are something like 10^17 > trigrams. It will never see enough data to build a model capturing > much semantics, unless it builds an incredibly compact model, > in which case-- what is the underlying structure and how > (computationally) are you going to learn it? Absolutely correct. That's why I said "My belief is that if you had the proper structure-building learning algorithms that your operator grammar system would simply (re-)discover the basic parts of speech and would then successfully proceed from there." and why I slammed it for ""reinventing the wheel" in terms of it's unnecessary generalization of dependency" > In unsupervised learning, you can learn a lot, > say you can cluster the world into two clusters. But until you get > supervision, you can't learn the final few bits to distinguish good > from bad, or whatever. I'm afraid that I disagree completely with the latter sentence. > Operator grammar might be very useful for > getting a structure that could then be rapidly trained to produce > meaning, but I don't think you can finish the job until you interact > with sensation. It seems as if you're now talking sensory fusion (which is a whole 'nother can o' worms). Mark - 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
Re: [agi] Parsing theories
>> Also, I don't see how you can call a model "semantic" when it makes >> no reference to the world. Mark> Ah, but this is where it gets tricky. While the model makes no Mark> reference to the world, it is certainly influenced by the fact Mark> that 100% of it's data comes from the world -- which then forces Mark> the model to build itself based upon the world Mark> (i.e. effectively, it is building a world model) -- and I would Mark> certainly call that semantics. As I think about it, one problem is, depending on how its parametrized, its not going to build much of a world model. Say for example it uses trigrams. The average hs grad knows something like 50,000 words. So there are something like 10^17 trigrams. It will never see enough data to build a model capturing much semantics, unless it builds an incredibly compact model, in which case-- what is the underlying structure and how (computationally) are you going to learn it? >> natural or highly unlikely, but unless I misunderstand something, >> there is no possibility it could tell me whether a sentence >> describes a scene. Mark> Do you mean that it couldn't perform sensory fusion or that it Mark> can't recognize "meaning"? I would agree with the former but Mark> (as an opinion -- because I can't definitively prove it) Mark> disagree with the latter. If adequately trained (a big if) it could perhaps distinguish a meaningful sentence from an unlikely one. The situation might be analagous to unsupervised learning. In unsupervised learning, you can learn a lot, say you can cluster the world into two clusters. But until you get supervision, you can't learn the final few bits to distinguish good from bad, or whatever. Operator grammar might be very useful for getting a structure that could then be rapidly trained to produce meaning, but I don't think you can finish the job until you interact with sensation. Mark> Mark - 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
Re: [agi] Parsing theories
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. That is really a philosophical point: it seems to be a special case of linguistic structuralism http://en.wikipedia.org/wiki/Structuralism in the spirit of Saussure In this approach one studies language as a system of interrelating signs ... e.g. "large" is defined in terms of its relationship to "small" and "huge" rather than in terms of its relationship to the physical world So yeah: you can't tell from linguistic structure alone if a sentence describes a real scene or an imaginary scene. But you might be able to tell if it defines a scene or not by looking at the collection of linguistic relationships generally needed to define a scene... I tend to think that structuralist linguistics points out some important aspects that are commonly overlooked in other linguistic paradigms, but also somewhat overstates things... Arguably Saussure was the grand-daddy of corpus linguistics... -- Ben G - 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
Re: [agi] Parsing theories
I'll take a shot at answering some of your questions as someone who has done some work and research but is certainly not claiming to be an expert . . . . 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.) Operator grammar in many respects reminds me of conceptual classification systems in that there has been success in processing huge amounts (corpuses, corpi? :-) of data and producing results -- but it's *clearly* not the way in which humans (i.e. human children) do it. My belief is that if you had the proper structure-building learning algorithms that your operator grammar system would simply (re-)discover the basic parts of speech and would then successfully proceed from there. I suspect that doing so is probably even computationally feasible (particularly if you accidentally bias it -- which would be *really* tough to avoid). All human languages fundamentally have the same basic parts of speech. I believe that operator grammar is "reinventing the wheel" in terms of it's unnecessary generalization of dependency. Is there empirical work with this model? It depends upon what you mean. My current project is "posit an underlying structure" of the basic parts of speech. Does it count -- or would I need to (IMO foolishly ;-) discard that for it to count? Also, I don't see how you can call a model "semantic" when it makes no reference to the world. Ah, but this is where it gets tricky. While the model makes no reference to the world, it is certainly influenced by the fact that 100% of it's data comes from the world -- which then forces the model to build itself based upon the world (i.e. effectively, it is building a world model) -- and I would certainly call that semantics. natural or highly unlikely, but unless I misunderstand something, there is no possibility it could tell me whether a sentence describes a scene. Do you mean that it couldn't perform sensory fusion or that it can't recognize "meaning"? I would agree with the former but (as an opinion -- because I can't definitively prove it) disagree with the latter. Mark - Original Message - From: "Eric Baum" <[EMAIL PROTECTED]> To: Sent: Wednesday, May 23, 2007 9:36 AM Subject: Re: [agi] Parsing theories 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 co
Re: [agi] Parsing theories
A google search on "operator grammar" + trigram yields nada. A google search on "operator grammar" + bigram yields nothing interesting. I've seen papers on statistical language parsing before, including trigrams etc. Not so clear to me the extent to which they've been merged with Harris's work. Jean-Paul> Check "bigrams" (or, more interestingly, "trigrams") in Jean-Paul> computational linguistics. Jean-Paul> Department of Information Systems Email: Jean-Paul> [EMAIL PROTECTED] Phone: (+27)-(0)21-6504256 Jean-Paul> Fax: (+27)-(0)21-6502280 Office: Leslie Commerce 4.21 Eric Baum <[EMAIL PROTECTED]> 2007/05/23 15:36:20 >>> Jean-Paul> One way to parametrize the likelihood of various arguments Jean-Paul> would be with a table over all two word combinations, the Jean-Paul> i,j entry gives the likelihood that the ith word and the Jean-Paul> jth word are the two arguments. But most likely, in Jean-Paul> reality, the likelihood of the jth word will be much pinned Jean-Paul> down conditional on the ith. Jean-Paul> Is there empirical work with this model? - 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
Re: [agi] Parsing theories
Check "bigrams" (or, more interestingly, "trigrams") in computational linguistics. Department of Information Systems Email: [EMAIL PROTECTED] Phone: (+27)-(0)21-6504256 Fax: (+27)-(0)21-6502280 Office: Leslie Commerce 4.21 >>> Eric Baum <[EMAIL PROTECTED]> 2007/05/23 15:36:20 >>> 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. Is there empirical work with this model? - 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
Re: [agi] Parsing theories
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
Re: [agi] Parsing theories
On 5/22/07, Matt Mahoney <[EMAIL PROTECTED]> wrote: Link grammar has a website and online demo at http://www.link.cs.cmu.edu/link/submit-sentence-4.html But as I posted earlier, it gives the same parse for: - I ate pizza with pepperoni. - I ate pizza with a friend. - I ate pizza with a fork. which shows that you can't separate syntax and semantics. Many grammars have this problem. Link grammar (similarily to CFG and most other approaches that don't already do it) can be extended with feature structures to be unified online in the run of the parser (leading to so called unification grammars). Nothing stops you from putting semantical information into these structures as long as it is monotonic. (Of course you cannot machine-learn these structures out of pure air.) - 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
Re: [agi] Parsing theories
Unfortunately, no -- I knew Jones when he was at Bell Labs, so a lot of what I know about APNs isn't from published papers. Now he's moved on and BL is not what it used to be, and I have no idea what ever happened to all the work that got done there on APNs. Lucent sure isn't doing it, and AT&T (now Shannon) Labs trashed their AI section a few years back. Josh On Tuesday 22 May 2007 02:39:59 pm Chuck Esterbrook wrote: > On 5/22/07, J Storrs Hall, PhD <[EMAIL PROTECTED]> wrote: > > I'm not doing any active work on it at the moment, but my favorite approach > > has been Mark Jones' active production networks, which are one of those > > schemes that lies in the twilight between symbolic and connectionist. Like > > Copycat, it is based on a semantic net with spreading activation and variable > > connection strengths. The network looks like the tree of a grammar, with lots > > of extra links, and the text is fed in by sequentialy "lighting up" the > > terminal nodes that correspond to words. After each one, the network > > reconfigures itself to interpret the next word/phrase appropriately. > > > > There is no formal distinction between nodes holding syntactic and semantic > > information. Indeed, if you "light up" nodes corresponding to a semantic > > situation, the network can be jogged to produce sentences describing it. > > Sounds interesting. I found some papers on it, but couldn't locate a > home page for Jones or the software. Do you have any good URLs to > share that Google isn't coughing up? > > -Chuck > > - > 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/?&; > > - 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
Re: [agi] Parsing theories
Any opinions on Operator Grammar vs. Link Grammar? A Link Grammar parser is relatively easy to implement and has low system requirements. Link Grammar uses (and depends upon) the phenomenon of planarity to (reasonably effectively) identify the parts of speech in English grammar. As such, it primarily deals with syntax (simpler) rather than semantics (much tougher). Operator Grammar deals much more with semantics. My personal opinion is that -- contrary to what is stated in Wikipedia (where it says "The categories in Operator Grammar are universal and are defined purely in terms of how words relate to other words, and do not rely on an external set of categories such as noun, verb, adjective, adverb, preposition, conjunction, etc. The dependency properties of each word are observable through usage and therefore learnable") -- the most effective way to use Operator Grammar concepts is to implement them as the next step after a Link Grammar parser. While it may be true that "the dependency properties of each word are observable through usage and therefore learnable", it is my personal belief that the "external set of categories such as noun, verb, adjective, adverb, preposition, conjunction, etc" are pretty much universal and that re-learning them is a waste of time. Using the concepts of Operator Grammar can help disambiguate situations where the Link Parser returns several viable parses, can help to learn new words, and an important step in moving from syntax (which is all that the Link Grammar parser really does) to semantics (which is really what Operator Grammar does) and then meaning and understanding. I actually re-invented (in a manner of speaking) dependency before I ran across it in Operator Grammar and have subsequently learned much from Harris's treatments of both dependency and reduction and have implemented a lot of them in my current project. So -- again, in my opinion -- Link Grammar wins the Google fight because it is much easier; but, you really need both to get anywhere (plus a huge dose of Construction Grammar -- which you'll notice just barely wins a Google fight with Link Grammar :-). Mark - Original Message - From: "Chuck Esterbrook" <[EMAIL PROTECTED]> To: Sent: Monday, May 21, 2007 10:24 PM Subject: [agi] Parsing theories 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? http://www.googlefight.com/index.php?lang=en_GB&word1=%22link+grammar%22&word2=%22operator+grammar%22 (http://tinyurl.com/yvu9xr) -Chuck - 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/?&; - 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=fabd7936
Re: [agi] Parsing theories
On 5/22/07, J Storrs Hall, PhD <[EMAIL PROTECTED]> wrote: I'm not doing any active work on it at the moment, but my favorite approach has been Mark Jones' active production networks, which are one of those schemes that lies in the twilight between symbolic and connectionist. Like Copycat, it is based on a semantic net with spreading activation and variable connection strengths. The network looks like the tree of a grammar, with lots of extra links, and the text is fed in by sequentialy "lighting up" the terminal nodes that correspond to words. After each one, the network reconfigures itself to interpret the next word/phrase appropriately. There is no formal distinction between nodes holding syntactic and semantic information. Indeed, if you "light up" nodes corresponding to a semantic situation, the network can be jogged to produce sentences describing it. Sounds interesting. I found some papers on it, but couldn't locate a home page for Jones or the software. Do you have any good URLs to share that Google isn't coughing up? -Chuck - 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=fabd7936
Re: [agi] Parsing theories
--- 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? > http://www.googlefight.com/index.php?lang=en_GB&word1=%22link+grammar%22&word2=%22operator+grammar%22 > (http://tinyurl.com/yvu9xr) Link grammar has a website and online demo at http://www.link.cs.cmu.edu/link/submit-sentence-4.html But as I posted earlier, it gives the same parse for: - I ate pizza with pepperoni. - I ate pizza with a friend. - I ate pizza with a fork. which shows that you can't separate syntax and semantics. Many grammars have this problem. Operator grammar seems to me to be a lot closer to the way natural language actually works. It includes semantics. The basic constraints (dependency, likelihood, and reduction) are all learnable. It might have gotten less attention because its main proponent, Zellig Harris, died in 1992, just before it became feasible to test the grammar in computational models (e.g. perplexity or text compression). Also, none of his publications are online, but you can find reviews of his books at http://www.dmi.columbia.edu/zellig/ -- Matt Mahoney, [EMAIL PROTECTED] - 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=fabd7936
Re: [agi] Parsing theories
I'm not doing any active work on it at the moment, but my favorite approach has been Mark Jones' active production networks, which are one of those schemes that lies in the twilight between symbolic and connectionist. Like Copycat, it is based on a semantic net with spreading activation and variable connection strengths. The network looks like the tree of a grammar, with lots of extra links, and the text is fed in by sequentialy "lighting up" the terminal nodes that correspond to words. After each one, the network reconfigures itself to interpret the next word/phrase appropriately. There is no formal distinction between nodes holding syntactic and semantic information. Indeed, if you "light up" nodes corresponding to a semantic situation, the network can be jogged to produce sentences describing it. Josh On Monday 21 May 2007 10:24:21 pm Chuck Esterbrook wrote: > Any opinions on Operator Grammar vs. Link Grammar? - 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=fabd7936
Re: [agi] Parsing theories
On 5/22/07, Chuck Esterbrook <[EMAIL PROTECTED]> wrote: Any opinions on Operator Grammar vs. Link Grammar? http://en.wikipedia.org/wiki/Operator_Grammar If you are intrested in Operator Grammar, perhaps you would also want to take a look at Grammatical Framework: http://www.cs.chalmers.se/~aarne/GF/ P.S. My first response might be too quick. Operator Grammar is certainly worth taking a closer look (it skipped my attention before). - 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=fabd7936
Re: [agi] Parsing theories
On 5/22/07, 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 That wiki article is too little to judge, but I'd say that operator grammar takes most ideas from dependency grammar and some (stress on semantics) from categorial grammar. It is also probabilistic by default, while other approaches add probabilities as an after-thought. But operator grammar is not a "main player in the field" (correct me if I'm wrong). The main players are: HPSG, LFG, xTAG, dependency grammars (including multidimensional), CCG. The entry point are "context free" unification grammars. For what I know, link grammar has not yet been "lifted" into a unification grammar. -- "Any sufficiently advanced linguistic framework is indistinguishable from HPSG." (an application of Clarke's third law) - 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=fabd7936
Re: [agi] Parsing theories
Handling syntax separately from semantics and pragmatics is hacky and non-AGI-ish ... but, makes it easier to get NLP systems working at a primitive level in a non-embodied context Operator grammar mixes syntax and semantics which is philosophically correct, but makes things harder Link grammar is purely syntactic, which is philosophically wrong, but makes things implementationally easier I have worked a lot with the link parser and it is pretty good for a rule-based statistical parser. But this kind of NLP framework has intrinsic limitations. The way we intend to ultimately do NLP in Novamente has more in common with operator grammar ... but we have used the link parser for commercial NLP projects, because it (sorta) works... -- Ben G On 5/21/07, 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? http://www.googlefight.com/index.php?lang=en_GB&word1=%22link+grammar%22&word2=%22operator+grammar%22 (http://tinyurl.com/yvu9xr) -Chuck - 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/?&; - 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=fabd7936