> The current link-grammar dict contains about 2.2K hand-edited, hand-curated rules. I believe that it is the worlds most-accurate English-language parser.
I do think that's impressive. I'm just not sure how I would actually work with the parser's output. On Tue, 5 Feb 2019 at 23:23, Linas Vepstas <[email protected]> wrote: > > > On Tue, Feb 5, 2019 at 12:01 PM Matt Mahoney <[email protected]> > wrote: > >> It is easy to come up with ideas and to say what approaches to AGI >> should be obvious. It is much harder to test them, and when we do we >> are sometimes surprised that our ideas don't work. Linas's >> dissertation length paper on the equivalence of symbolic and neural >> language systems would be a good review of dozens of different >> approaches > > > Well, its a review of *two* approaches, not dozens: vector-space > approaches, and monoidal category approaches. Vector spaces are a special > case of monoidal categories. I'm trying to indicate that they are a > straight-jacket, as a result. They also fail to align with traditional > linguistics theory. (The earliest reference I know that states that > "traditional lingusitics" is a monoidal category dates to 1967, and is in > the form of an entire book devoted to the topic.) The current obsession > with neural nets appears to be due to the fact that the practioners are > unaware of the category-theoretic formulations for vector spaces. I figure > its a matter of time, before there is a sea-change. > > > >> if there were an experimental results section that told us >> which ones were worth pursuing. > > > There's this: > > > https://github.com/opencog/opencog/raw/master/opencog/nlp/learn/learn-lang-diary/connector-sets-revised.pdf > > > https://github.com/opencog/opencog/raw/master/opencog/nlp/learn/learn-lang-diary/learn-lang-diary.pdf > > There's a team that has taken over the project; unfortunately, this still > are getting up to speed, and haven't made any progress yet. > > >> Rule based grammars seem to make sense because it works on artificial >> languages using very little computing power. > > > Rule-based grammars are monoidal categories. Neural nets are vector-space > algorithms, which are *SPECIAL CASES* of monoidal categories. That's the > key take-away message. The reason my "dissertation" is so long is that I > need to build a lot of vocabulary and terminology to explain how a vector > space is "the same thing" as a "rule". This is mostly because most readers > in linguistics don't know what a tensor algebra is, and most readers in > neural nets don't know what a tensor algebra is .. despite products with > names like "TensorFlow". > > A tensor is a rule. Full stop. > > >> You parse the sentence >> and analyze the tree for semantics. You can cover about half of all >> English sentences with a few dozen rules. But English doesn't work >> that way. Nobody knows how many rules you need to parse the other >> half. > > > The current link-grammar dict contains about 2.2K hand-edited, > hand-curated rules. I believe that it is the worlds most-accurate > English-language parser. > > >> >> The standard measure of language model performance is word perplexity, >> or equivalently, text prediction or compression. > > > Its a truly shitty measure, created by people who do not understand what > linguistics has been up to for the last 70 years. Don't waste your time on > pseudo-science. > > I can't respond to the rest, because it seems to be based on this key > mis-understanding. > > -- Linas > > > -- > cassette tapes - analog TV - film cameras - you > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > <https://agi.topicbox.com/groups/agi/Ta6fce6a7b640886a-M011f878ccde9ddb9602e47f7> > -- Stefan Reich BotCompany.de // Java-based operating systems ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Ta6fce6a7b640886a-M9255632e375ca19d05cacfc9 Delivery options: https://agi.topicbox.com/groups/agi/subscription
