you should start with simple factored models 1st, perhaps using only 1
translation model with 2 factors. Then move onto 1 translation model and
1 generation model.
The factored you are difficult to control, they use a lot of memory and
takes a lot of time. You may be getting errors because it runs out of
memory.
On 28/12/15 10:01, gozde gul wrote:
Hi,
I am trying to perform a 3 factored translation from English to
Turkish. My example input is as follows:
En: Life+NNP|Life|NNP end+VBZ_never+RB|end|VBZ_never+RB but+CC|but|CC
earthly+JJ|earthly|JJ life+NN|life|NN do+VBZ|do|VBZ .+.|.|.
Tr: Hayat|hayat|+Noun+A3sg+Pnon+Nom hiç|hiç|+Adverb
bitmez|bit|+Verb+Neg+Aor+A3sg fakat|fakat|+Conj
dünyadaki|dünya|+Noun+A3sg+Pnon+Loc^DB+Adj+Rel
hayat|hayat|+Noun+A3sg+Pnon+Nom biter|bit|+Verb+Pos+Aor+A3sg .|.|+Punc
My translation and generation factors and decoding steps are as
follows. I am pretty sure they are correct:
--translation-factors 1-1+2-2+0-0 \
--generation-factors 1,2-0 \
--decoding-steps t2:t0,t1,g0
I have created language models for all 3 factors with irstlm with the
steps explained in moses website.
If I train with the following model, it creates a moses.ini. When I
manually check the phrase tables and generation table they look
meaningful.
~/mosesdecoder/scripts/training/train-model.perl \
--parallel --mgiza \
--external-bin-dir ~/workspace/bin/training-tools/mgizapp \
--root-dir ~/FactoredModel/SmallModel/ \
--corpus
~/FactoredModel/SmallModel/factored-corpus/training/korpus_1000K.en-tr.KO.recleaned_new
\
--f en --e tr --alignment grow-diag-final-and \
--reordering msd-bidirectional-fe \
--lm 0:3:$HOME/corpus/FilteredCorpus/training/lm/surLM/sur.lm.blm.tr:8
<http://sur.lm.blm.tr:8/> \
--lm
1:3:$HOME/corpus/FilteredCorpus/training/lm/lemmaLM/lemma.lm.blm.tr:8
<http://lemma.lm.blm.tr:8/> \
--lm
2:3:$HOME/corpus/FilteredCorpus/training/lm/postagLM/postags.lm.blm.tr:8
<http://postags.lm.blm.tr:8/> \
--alignment-factors 1-1 \
--translation-factors 1-1+2-2+0-0 \
--generation-factors 1,2-0 \
--decoding-steps t2:t0,t1,g0 >& ~/FactoredModel/trainingSmall3lm.out
But when I try to decode a very simple one-line sentence, I get a
"Segmentation fault (Core Dumped)" message. You can see the detailed
decoding log here
<https://www.dropbox.com/s/2xgi681k2ssus5z/error.txt?dl=0>. I tried
many things and I'm in a dead end, so I would really appreciate your help.
Thanks,
Gozde
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--
Hieu Hoang
http://www.hoang.co.uk/hieu
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