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
>>
>> _______________________________________________
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>> [email protected]
>> http://mailman.mit.edu/mailman/listinfo/moses-support
>>
>>
>
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