I'm getting this error on a EMS training during tuning phase, not sure if this 
configuration has sense, just trying to play with a POS tagger and with 
factored models:

Executing: /opt/moses/bin/moses -v 0   -config 
/mnt/a62/devel/en_es/tuning/moses.filtered.ini.1 -weight-overwrite 
'GenerationModel0= 0.038462 LM1= 0.064103 TranslationModel2= 0.025641 0.025641 
0.025641 0.025641 TranslationModel1= 0.025641 0.025641 0.025641 0.025641 
WordPenalty0= -0.128205 LM2= 0.064103 Distortion0= 0.038462 TranslationModel0= 
0.025641 0.025641 0.025641 0.025641 LexicalReordering0= 0.038462 0.038462 0.038462 
0.038462 0.038462 0.038462 LM0= 0.064103 GenerationModel1= 0.038462 0.000000 
PhrasePenalty0= 0.025641'  -n-best-list run1.best100.out 100 distinct  -input-file 
/mnt/a62/devel/en_es/data/corpora.tuning.en > run1.out
Can't read /mnt/a62/devel/en_es/model/generation.1-0
Exit code: 1
The decoder died. CONFIG WAS -weight-overwrite 'GenerationModel0= 0.038462 LM1= 
0.064103 TranslationModel2= 0.025641 0.025641 0.025641 0.025641 
TranslationModel1= 0.025641 0.025641 0.025641 0.025641 WordPenalty0= -0.128205 
LM2= 0.064103 Distortion0= 0.038462 TranslationModel0= 0.025641 0.025641 
0.025641 0.025641 LexicalReordering0= 0.038462 0.038462 0.038462 0.038462 
0.038462 0.038462 LM0= 0.064103 GenerationModel1= 0.038462 0.000000 
PhrasePenalty0= 0.025641' 
cp: cannot stat ‘/mnt/a62/devel/en_es/tuning/tmp.1/moses.ini’: No such file or 
directory


I'm trying to use a factored model from en to es with the following factors:

input-factors = pos lemma surface
output-factors = pos lemma surface
alignment-factors = "surface -> surface"
translation-factors = "surface -> surface, pos -> pos"
reordering-factors = "surface -> surface"
generation-factors = "surface -> pos"
decoding-steps = "t0,t1,g0"

The corpus has been previously cleaned and factored with the format:

pos0|lemma0|surface0 pos1|lemma1|surface1 pos2|lemma2|surface2 ... 
posN|lemmaN|surfaceN

before factoring I've filtered the corpus to filter characters like | < > [] .... 
and also filtered the segments with length > 80




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