Dear Shaimaa,
Adding factors can only increase any out-of-vocabulary issues.
Use -v (perhaps even a higher verbosity level) in moses to see what all
translation options are considered for the problematic sentence. There could be
some unfortunate weight settings that for some reason prefer identity
translation. (The identity translation must however appear in the data, or the
source word must not appear in the data, otherwise Moses would not produce
identity translation at all.)
And then go back to the phrase table and manually search for the lines that are
supposed to cover the missing words. Here you may find the identity entries.
And then go back and check the word alignment this (test) sentence got in the
training data. There are most likely some issues with the alignment that
prevented proper translations to be extracted.
Best, Ondrej.
On January 6, 2016 4:48:26 AM CET, Shaimaa Marzouk wrote:
>Dear Moses-Team,
>
>I am trying to translate two short sentences included in the same file
>from German into English using a “Phrase-based Model”. The first
>sentence (das auto wurde verkauft) is translated correctly, while the
>second is partly translated:
>
>I receive as a result for “ich habe das auto verkauft”
>Ich|UNK|UNK|UNK habe|UNK|UNK|UNK the car sold [1]
>[total=-203.330] core=(-200.000, -5.000, 5.000, 0.000, 0.000, 0.000,
>0.000, 0.000, -18.660)
>
>I tried to modify the training data in different ways, and at last
>included the exact sentence (along with its translation) in the
>training data (see attachment). But, I still get the same result.
>
>Do I need to use a “Factored Translation Model” instead of the
>“Phrase-based Model” to be able to translate this sentence? If yes, I
>find here http://www.statmt.org/moses/?n=Moses.FactoredTutorial
>explanation of how to train Factored Models. Could you please tell me,
>where can I find information about
>1. how to prepare the training data with additional factors, before
>training the Factored Model?
>2. how to train the Language Model that considers the POS?
>
>I currently use KenLM and Giza++.
>
>Thanks a lot for your support.
>
>Kind regards,
>Shaimaa
>
>
>
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--
Ondrej Bojar (mailto:o...@cuni.cz / bo...@ufal.mff.cuni.cz)
http://www.cuni.cz/~obo
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