Hi all,
I have a question concerning the "Tutorial for Using Factored Models",
section on "Train a morphological analysis and generation model".
The following translation factors and generation factors are trained for
the given example corpus:
--translation-factors 1-1+3-2 \
--generation-factors 1-2+1,2-0 \
--decoding-steps t0,g0,t1,g1
What is the advantage of using the first generation factor 1-2 compared
to the configuration below?
--translation-factors 1-1+3-2 \
--generation-factors 1,2-0 \
--decoding-steps t0,t1,g1
I understand the 1-2 generation factor maps lemmas to POS+morph
information, but the same information is also generated by the 3-2
translation factor. Apart from that this generation factor introduces
huge combinatorial blow-up, since every lemma can be mapped to basically
every possible morphological information seen for this lemma.
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