On Tuesday, 11 February 2020 18:45:44 UTC+1, linas 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).
>

Is using English language as the target too limited (overfitting)? There 
are datasets for grammatical tasks like Part Of Speech tagging, the quality 
of the grammar could be judged by testing performance on those tasks.


> 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 <[email protected] 
> <javascript:>> 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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>
>
> -- 
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