Hi, Ezgi, if you are not using output factor 1, try avoiding it in the configuration at all, so use 0-0+1-1 and 1:9:...pos.lm. Also, check if you moses.ini contains
[output-factors] 0 1 2 And try verbose output to see if indeed Moses produces all the three factors, not just that they are in the training data. Actually, I am quite sure that the factor 1 is null with your current setup. The error comes probably from the fact that Moses too eagerly looks at it. Cheers, Ondrej. ----- Original Message ----- > From: "ezgi yıldırım" <ezgiyil...@gmail.com> > To: moses-support@mit.edu > Sent: Tuesday, 21 January, 2014 1:44:54 PM > Subject: [Moses-support] factored models with pos lm > > Hi all, > > I've problem with factored models. I used an English-Turkish parallel > corpus with three factors (surface|lemma|pos) on both sides. I trained the > decoder with --translation-factors 0-0+2-2 from English to Turkish and > specified two language models, one for surface factor and other one for pos > factor. Here is my training command: > > mosesdecoder/scripts/training/train-model.perl --parallel --mgiza > --mgiza-cpus 32 --external-bin-dir ../../usr/local/bin/ --root-dir > $working/ --corpus $working/corpus/$name.en-tr.lowercased --f en --e tr > --alignment grow-diag-final-and --reordering msd-bidirectional-fe --lm > 0:5:/home/ezgi/$working/lm/$name-surface.en-tr.lm:0 --lm > 2:9:/home/ezgi/working/working_v4/lm/$name-pos.en-tr.lm:0 > --translation-factors 0-0+2-2 >& $working/training.out > > However, I got this error while the first instance of tuning step is > processing: > > Check (*contextFactor[count-1])[factorType] != NULL failed in > moses/LM/SRI.cpp:155 > Aborted > Exit code: 134 > The decoder died. CONFIG WAS -w -0.217391 -lm 0.054348 0.054348 -d 0.065217 > 0.065217 0.065217 0.065217 0.065217 0.065217 0.065217 -tm 0.043478 0.043478 > 0.043478 0.043478 0.043478 > > I checked that all the factored forms already have three factors. What is > the meaning of this error message? I supposed I made a mistake while > building pos lm, but I'm using witten-bell discounting which is the most > appropriate method for LMs with small vocabulary such as pos-lm. > > This is the command I used to build pos-lm: > > tools/srilm/bin/i686-m64/ngram-count -order 9 -interpolate -wbdiscount > -text $working/lm/$name-pos.en-tr.lowercased.tr -lm > $working/lm/$name-pos.en-tr.lm > > I will be pleased if you help me on this. > Regards, > > Ezgi > > _______________________________________________ > Moses-support mailing list > Moses-support@mit.edu > http://mailman.mit.edu/mailman/listinfo/moses-support > -- Ondrej Bojar (mailto:o...@cuni.cz / bo...@ufal.mff.cuni.cz) http://www.cuni.cz/~obo _______________________________________________ Moses-support mailing list Moses-support@mit.edu http://mailman.mit.edu/mailman/listinfo/moses-support
