Thank you! Marco On Wed, 29 Jul 2015 4:58 pm Philipp Koehn <[email protected]> wrote:
> Hi, > > there is no specific existing feature function that allows for exactly > that. > > The closest approximation would be to use the WordTranslation feature > for this factor. This would learn binary features for each mapping of > one annotation to the other, hopefully learning to prefer some mappings > (where they agree) to others. > > You can set this in EMS with: > > sparse-features = "word-translation all factor 1-1" > > where "1" is the factor number for your annotation. > > If you want to implement exactly what you describe, you should look > at the word translation feature, and write a very similar feature function. > > -phi > > On Fri, Jul 24, 2015 at 6:03 AM, Marco Damonte <[email protected]> wrote: > >> Hi everyone, >> >> I'm using EMS to run experiments involving semantic annotations as >> factors. I would like to try adding sparse features to use the fact that >> when a word and its translation have the same annotation, there is good >> chances that it is a good translation. >> >> I read the tutorials on Moses website but it's still not clear to me how >> this works. Can anyone help me with this? >> >> Regards, >> Marco >> >> _______________________________________________ >> Moses-support mailing list >> [email protected] >> http://mailman.mit.edu/mailman/listinfo/moses-support >> >> >
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