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N-Gram approach for better English translation #106

@sidprasad

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@sidprasad

Currently our English to LTL translation is lacking. For instance, the
formula F(n → Gz), translates to “Eventually, globally, z holds is necessary for n holds”. We readily acknowledge that this recursively-generated phrasing is both confusing and unnatural.


I wonder if (given the small amount of randomness we already have in generating English) we could generate a few candidate English translations and then use a reasonable metric (maybe n-grams? smoothing?) to choose the best / most natural one?
I think relatively little work has been done in the world of LTL to English. Issues include :

  • Compositionality gap: English is not fully compositional for temporal semantics
  • English handles time through implicit quantifiers, whereas LTL requires explicit ones.
  • Human language uses event schemas and narrative structure; LTL uses positions on a trace.
  • English negation is structure-sensitive.

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