Mike, If your question is directed toward the general AI community (rather then the people on this list), the answer is a definite YES. It was some time ago, and as far as I know the line of research has been dropped, yet the results are to this day quite surprisingly good (I think). The following site has an example.
http://www.it.uu.se/edu/course/homepage/ai/vt07/SCHANK.HTM The details of the story can vary fairly significantly and still the system performs as well as it does here (so long as it is still a story about traveling to get something to eat, written with the sorts of grammatical constructs you see in that story). Of course, this is a result of a fair amount of effort, programming "scripts" for everyday events. The approach was dropped because too much knowledge entry would be required to be practical for reading, say, a random newspaper story. But that is just what Cyc is for. Anyway, the point is, understanding passages is not a new field, just a neglected one. --Abram On Mon, Sep 29, 2008 at 3:23 PM, Mike Tintner <[EMAIL PROTECTED]> wrote: > Ben and Stephen, > > AFAIK your focus - and the universal focus - in this debate on how and > whether language can be symbolically/logically interpreted - is on > *individual words and sentences.* A natural place to start. But you can't > stop there - because the problems, I suggest, (hard as they already are), > only seriously begin when you try to interpret *passages* - series of > sentences from texts - and connect one sentence with another. Take: > > "John sat down in the carriage. His grim reflection stared at him through > the window. A whistle blew. The train started shuddering into motion, and > slowly gathered pace. He was putting Brighton behind him for good. And just > then the conductor popped his head through the door." > > I imagine you can pose the interpretative questions yourself. How do you > connect any one sentence with any other here? Where is the whistle blowing? > Where is the train moving? Inside the carriage or outside? Is the > carriage inside or outside or where in relation to the moving train? Was he > putting Brighton *physically* behind him like a cushion? Did the conductor > break his head? etc. etc. > > The point is - in reading passages, in order to connect up sentences, you > have to do a massive amount of *reading between the lines* . In doing that, > you have to reconstruct the world or parts of the world, being referred to, > from your brain's own models of that world.. (To understand the above > passage, for example, you employ a very complex model of train travel). > > And this will apply to all kinds of passages - to arguments as well as > stories. (Try understanding Ben's argument below). > > How does Stephen or YKY or anyone else propose to "read between the lines"? > And what are the basic "world models", "scripts", "frames" etc etc. that you > think sufficient to apply in understanding any set of texts, even a > relatively specialised set? > > (Has anyone seriously *tried* understanding passages?) > > > Stephen, > > Yes, I think your spreading-activation approach makes sense and has plenty > of potential. > > Our approach in OpenCog is actually pretty similar, given that our > importance-updating dynamics can be viewed as a nonstandard sort of > spreading activation... > > I think this kind of approach can work, but I also think that getting it to > work generally and robustly -- not just in toy examples like the one I gave > -- is going to require a lot of experimentation and trickery. > > Of course, if the AI system has embodied experience, this provides extra > links for the spreading activation (or analogues) to flow along, thus > increasing the odds of meaningful results... > > Also, I think that spreading-activation type methods can only handle some > cases, and that for other cases one needs to use explicit inference to do > the disambiguation. > > My point for YKY was (as you know) not that this is an impossible problem > but that it's a fairly deep AI problem which is not provided out-of-the-box > in any existing NLP toolkit. Solving disambiguation thoroughly is AGI-hard > ... solving it usefully is not ... but solving it usefully for > *prepositions* is cutting-edge research going beyond what existing NLP > frameworks do... > > -- Ben G > > On Mon, Sep 29, 2008 at 1:25 PM, Stephen Reed <[EMAIL PROTECTED]> wrote: >> >> Ben gave the following examples that demonstrate the ambiguity of the >> preposition "with": >> >> People eat food with forks >> >> People eat food with friend[s] >> >> People eat food with ketchup >> >> The Texai bootstrap English dialog system, whose grammar rule engine I'm >> currently rewriting, uses elaboration and spreading activation to perform >> disambiguation and pruning of alternative interpretations. Let's step >> through how Texai would process Ben's examples. According to Wiktionary, >> "with" has among its word senses the following: >> >> as an instrument; by means of >> >> in the company of; alongside; along side of; close to; near to >> >> in addition to, as an accessory to >> >> Its clear when I make these substitutions which word sense is to be >> selected: >> >> People eat food by means of forks >> >> People eat food in the company of friends >> >> People eat ketchup as an accessory to food >> >> Elaboration of the Texai discourse context provides additional entailed >> propositions with respect to the objects actually referenced in the >> utterance. The elaboration process is efficiently performed by spreading >> activation over the KB from the focal terms with respect to context. The >> links explored by this process can be formed by offline deductive inference, >> or learned from heuristic search and reinforcement learning, or simply >> taught by a mentor. >> >> Relevant elaborations I would expect Texai to make for the example >> utterances are: >> >> a fork is an instrument >> >> there are activities that a person performs as a member of a group of >> friends; to eat is such an activity >> >> ketchup is a condiment; a condiment is an accessory with regard to food >> >> Texai considers all interpretations simultaneously, in a transient >> spreading activation network whose nodes are the semantic propositions >> contained within the elaborated discourse context and whose links are formed >> when propositions share an argument concept. Negative links are formed >> between propositions from alternative interpretations. At AGI-09 I hope to >> demonstrate this technique in which the correct word sense of "with" can be >> determined from the highest activated nodes in the elaborated discourse >> context after spreading activation has quiesced. >> >> -Steve >> >> Stephen L. Reed >> Artificial Intelligence Researcher >> http://texai.org/blog >> http://texai.org >> 3008 Oak Crest Ave. >> Austin, Texas, USA 78704 >> 512.791.7860 >> >> ----- Original Message ---- >> From: Ben Goertzel <[EMAIL PROTECTED]> >> To: [email protected] >> Sent: Monday, September 29, 2008 8:18:30 AM >> Subject: Re: [agi] universal logical form for natural language >> >> >> >> On Mon, Sep 29, 2008 at 4:23 AM, YKY (Yan King Yin) >> <[EMAIL PROTECTED]> wrote: >>> >>> On Mon, Sep 29, 2008 at 4:10 AM, Abram Demski <[EMAIL PROTECTED]> >>> wrote: >>> > >>> > How much will you focus on natural language? It sounds like you want >>> > that to be fairly minimal at first. My opinion is that chatbot-type >>> > programs are not such a bad place to start-- if only because it is >>> > good publicity. >>> >>> I plan to make use of Steven Reed's Texai -- he's writing a dialog >>> system that can translate NL to logical form. If it turns out to be >>> unfeasible, I can borrow a simple NL interface from somewhere else. >> >> >> Whether using an NL interface like Stephen's is feasible or not, really >> depends on your expectations for it. >> >> Parsing English sentences into sets of formal-logic relationships is not >> extremely hard given current technology. >> >> But the only feasible way to do it, without making AGI breakthroughs >> first, is to accept that these formal-logic relationships will then embody >> significant ambiguity. >> >> Pasting some text from a PPT I've given... >> >> *** >> Syntax parsing, using the NM/OpenCog narrow-AI RelEx system, transforms >> >> Guard my treasure with your life >> >> into >> >> _poss(life,your) >> _poss(treasure,my) >> _obj(Guard,treasure) >> with(Guard,life) >> _imperative(Guard) >> >> Semantic normalization, using the RelEx rule engine and the FrameNet >> database, transforms this into >> >> Protection:Protection(Guard, you) >> Protection:Asset(Guard, treasure) >> Possession:Owner(treasure, me) >> Protection:Means(Guard, life) >> Possession:Owner(life,you) >> _imperative(Guard) >> >> But, we also get >> >> Guard my treasure with your sword. >> >> Protection:Protection(Guard, you) >> Protection:Asset(Guard, treasure) >> Possession:Owner(treasure, me) >> Protection:Means(Guard, sword) >> Possession:Owner(sword,you) >> _imperative(Guard) >> >> Guard my treasure with your uncle. >> >> Protection:Protection(Guard, you) >> Protection:Protection(Guard, uncle) Protection:Asset(Guard, treasure) >> Possession:Owner(treasure, me) >> Protection:Means(Guard, sword) >> Possession:Owner(uncle,you) >> >> ***** >> >> The different senses of the word "with" are not currently captured by the >> RelEx NLP >> system, and that's a hard problem for current computational linguistics >> technology >> to grapple with. >> >> I think it can be handled via embodiment, i.e. via having an AI system >> observe >> the usage of various senses of "with" in various embodied contexts. >> >> Potentially it could also be handled via statistical-linguistics methods >> (where the >> contexts are then various documents the senses of "with" have occurred in, >> rather >> than embodied situations), though I'm more skeptical of this method. >> >> In a knowledge entry context, this means that current best-of-breed NL >> interpretation systems will parse >> >> People eat food with forks >> >> People eat food with friend >> >> People eat food with ketchup >> >> into similarly-structured logical relationships. >> >> This is just fine, but what it tells you is that **reformulating English >> into logical >> formalism does not, in itself, solve the disambiguation problem**. >> >> The disambiguation problem remains, just on the level of disambiguating >> formal-logic structures into less ambiguous ones. >> >> Using a formal language like CycL to enter knowledge is one way of largely >> circumventing this problem ... using Lojban would be another ... >> >> (Again I stress that having humans encode knowledge is NOT my favored >> approach to AGI, but I'm just commenting on some of the issues involved >> anyway...) >> >> -- Ben G >> >> >> ________________________________ >> agi | Archives | Modify Your Subscription >> ________________________________ >> agi | Archives | Modify Your Subscription > > > -- > Ben Goertzel, PhD > CEO, Novamente LLC and Biomind LLC > Director of Research, SIAI > [EMAIL PROTECTED] > > "Nothing will ever be attempted if all possible objections must be first > overcome " - Dr Samuel Johnson > > > ________________________________ > agi | Archives | Modify Your Subscription > > whist > ________________________________ > agi | Archives | Modify Your Subscription ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
