Hi Jimmy,

The example you borrowed from
http://www.statmt.org/jhuws/?n=Projects.Tuning seems to be out-of-date,
the output of the example I gave in my e-mail is very different from the
one in that example. :( 

In http://www.statmt.org/moses/?n=Moses.AdvancedFeatures there is no
explanation of which are the  individual components scores.


--
Felipe.

El mié, 12-11-2008 a las 11:29 +0000, Jimmy O'Regan escribió:
> 2008/11/12 Felipe Sánchez Martínez <[EMAIL PROTECTED]>:
> >
> > Hi all,
> >
> 
> Hi Felipe.
> 
> > I am working with an n-best list generated with Moses. My question is,
> > which are the individual component scores (unweigthed) obtained?
> >
> > Suppose the following entry in an n-best list:
> >
> > 4 ||| así .  ||| d: 0 -0.619042 0 0 0 0 0 lm: -11.4288 tm: -4.84733
> > -6.39323 -6.90676 -7.23185 0.999896 w: -2 ||| -2.40665
> >
> > * "4"
> >     -> the number of the sentence
> > * "así ."
> >     -> the output sentence
> > * "d: 0 -0.619042 0 0 0 0 0"
> >     -> No idea ¿?
> > * "lm: -11.4288"
> >     -> I suppose "lm:" stands for language model (log probability).
> >        Is this correct?
> > * "tm: -4.84733 -6.39323 -6.90676 -7.23185 0.999896"
> >      -> I suppose "tm:"  stands for translation model. But,
> >         to which translation model correspond each different value?
> > * "w: -2"
> >      -> I suppose "w:" stands from word penalty.
> > * "-2.40665"
> >      -> weighted overall socore.
> >
> 

> 
> "Example: d:1,0.5-1.5 lm:1,0.5-1.5
> tm:0.3,0.25-0.75;0.2,0.25-0.75;0.2,0.25-0.75;0.3,0.25-0.75;0,-0.5-0.5
> w:0,-0.5-0.5 sets
> one weight for the distortion model, starting with 1, then randomized
> from 0.5-1.5
> one weight for the language model, starting with 1, then randomized from 
> 0.5-1.5
> five weights for the translation model:
> the first starting at 0.3, then randomized from 0.25-0.75
> the first starting at 0.2, then randomized from 0.25-0.75
> the first starting at 0.2, then randomized from 0.25-0.75
> the first starting at 0.3, then randomized from 0.25-0.75
> the first starting at 0, then randomized from -0.5 to 0.5
> one weight for the word penalty, starting with 0, then randomized from
> -0.5 to 0.5"
> 
> >
> > I have been looking for this information in  the list archive but my
> > search was fruitless.
> >
> 

> might be useful, too.
-- 
Felipe Sánchez Martínez <[EMAIL PROTECTED]>
Departamento de Lenguajes y Sistemas Informáticos
Universidad de Alicante, E-03071 Alicante (Spain)
Tel.: +34 965 903 400, ext: 2038 Fax: +34 965 909 326
http://www.dlsi.ua.es/~fsanchez

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