I take it back, the field is still alive. Interesting. http://xenia.media.mit.edu/~mueller/storyund/storyres.html
--Abram Demski On Mon, Sep 29, 2008 at 9:51 PM, Abram Demski <[EMAIL PROTECTED]> wrote: > 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
