We would not want to add an entire natural language processing toolkit;
SymPy has a rather strict "no external dependencies" policy because it
needs to be installable in installer-unfriendly environments
(non-administrator accounts, mobile devices).
However, it would be extremely useful if we could "steal" the parser
engine from such a toolkit.
Most if not all of these engines accept arbitrary context-free grammars.
With such an engine, we could just write down the BNF of some grammar
(Mathematica, Latex, natural language, whatever), and experiment with it
until it works satisfactorily.
A general remark: Natural language is notoriously hard to parse. Either
it's intuitive, then it's too ambiguous to be useful in a context like
that of symbolic math; or it's precise, in which case it isn't natural
language anymore. Finding the right trade-off for such things is an
ongoing research topic. And after that, you get into the *really*
"interesting" problems...
My advice would be to avoid natural language if it's just a means to an
end; natural language processing just isn't explored well enough for
that, and you'll likely get more problems than the approach can solve.
If, on the other hand, natural language processing is your primary
interest, by all means continue with it, there's a lot of PhD material
in there :-)
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