Linas, we haven't been discussing this on public lists much, but
Andres Suarez and I are actually making some interesting progress on
the language learning project lately ... we are both here in HK so
most of the discussion is F2F ... we are using transformer-NN language
models as "sentence probability oracles" (they can estimate the
probability of a sentence according to a language model) and using
these oracles to estimate the probabilities of various sentences
proposed by the symbolic grammar-rule and POS learning algorithms,....
will have more to say on this in the coming months, but it's looking
like a pretty cool example of neural-symbolic methodology.



On Wed, Feb 12, 2020 at 1:46 AM Linas Vepstas <linasveps...@gmail.com> wrote:
>
> Salut Amirouche,
>
> What you describe was/is the goal of the language-learning project. It is 
> stalled, because there is no easy way to evaluate if it is making forward 
> progress, and is learning a good grammar, or learning junk.
>
> The proposed solution to this is to create "random" grammars, and thus 
> compare what the system learned to the precise, exactly-known grammar.  The 
> only problem here is that generating a corpus of sentences drawn from a given 
> grammar is surprisingly hard.  (i.e. is not an afternoon project, or even a 
> one-week project).
>
> I would love to work on this, but well, good old capitalistic considerations 
> are currently blocking my efforts.
>
> --linas
>
> On Tue, Feb 11, 2020 at 9:16 AM Amirouche Boubekki 
> <amirouche.boube...@gmail.com> wrote:
>>
>> I am wondering whether there is existing material about how to
>> bootstrap a LG-like dictionary using a seed of natural language
>> elements: grammar, words, punctuation....
>>
>> The idea is to use such a seed to teach the program more about the
>> full grammar using almost natural conversations.
>>
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