============================================ binrules: BIlingual N-gram rewrite RULES by jmcrego@limsi.fr, January 2011 ============================================ usage: binrules -wrd s -tag s -rrules s [-maxr i] [-maxc f] [-verbose] [-help] Input files: -wrd s : file to translate (word forms) -tag s : file to translate (POS tags) -rrules s : reordering rules Rules/Units filtering: -maxc f : max cost reordering rules [default 0] -maxr i : max size reordering rules [default 9] Other: -verbose : verbose output [default false] -silent : silent output [default false] -help : this help
de@8 ||| from ||| 0.4993 1.6338 3.8078 0.9002 ||| 0.2177 4.6121 1.6834 0.2054 1.8465 3.5772 ||| 412513 267 ||| from PRPThe first two fields consist of the source and target tuple words. Note that source words are also tagged with their position in the test sentence (mainly used by the decoder to apply the distortion penalty and to calculate the orientation type of the lexicalized reordering model). The next for scores correspond to the uncontextualized tuple translation models. The next six scores correspond to lexicalized reordering scores. next we find the tuple Ids used for the bilingual n-gram language model (with tuples built from words) and the second bilingual n-gram language model (with tuples built from pos tags). The last two fields correspond to two different factor forms of the tuple target side (using words 'from' and POS tags 'PRP').
================================================ binfiltr: BIlingual N-gram smt models FILTeR by jmcrego@limsi.fr, January 2011 ================================================ usage: binfiltr -tunits s [-maxs i] [-verbose] [-help] < flattice flattice s : file with input lattices -tunits s : translation units -scores s : unit scores -lexrm s : lexicalized RM scores -bilfactor s : bilingual factored units -srcfactor s : src factored units -trgfactor s : trg factored units -maxs i : max size translation units [default 5] -verbose : verbose output [default false] -help : this help
========================================== bincoder: BIlingual N-gram smt deCODER jmcrego[at]limsi[dot]fr (May 2011) ========================================== usage : bincoder [I/O] [Search settings] [Model files] [Model weights] [Other] I/O: -i s : input file -f i : first sentence to translate in input file (0:first of ifile) [default 0] -l i : last sentence to translate in input file (0:last of ifile) [default 0] -o s : output file -c s : config file Search settings: -s s : search strategy [default 2J] 'J' (J stacks) hyps covering the same number of source words '2J' (up to 2^J stacks) hyps covering the same source words -t i : consider i-best tuple translation choices (0:all choices) [default 25] -b i : expand at most i-best states of each stack (0:expand all) [default 50] Model files: -{b,t,s}lm(i) j[,k],s : i-th (b:bilingual, t:target, s:source) LM (factor j) (i>=0, j>=0) -s{b,t,s}lm(i) j[,k],s : i-th sent-based (b:bilingual, t:target, s:source) LM (factor j) (i>=0, j>=0) increase by k the cost of p(|...) [default 0] -s{b,t,s}xm(i) j,s : i-th sent-based (b:bilingual, t:target, s:source) XM (factor j) (i>=0, j>=0) Model weights: -l{b,t,s}(i) f : i-th (b:bilingual, t:target, s:source) LM (i>=0) -ls{b,t,s}(i) f : i-th sentence-based (b:bilingual, t:target, s:source) LM (i>=0) -lx{b,t,s}(i) f : i-th sentence-based (b:bilingual, t:target, s:source) XM (i>=0) -la(i) f : i-th tuple (uncontextualized) model (i>=0) -l{m,s,d,c,f,b}{c,p} f : lexicalized RM -lg f : input graph -ld f : distortion penalty -lp{0,1,2} f : bonus models (0:tuple, 1:target word, 2:source word) Other: -dropoov : drop OOV (source) words [default 0] -ograph : ouput graph in ofile.GRAPH [default 0] -nbest i : ouput i-best hyps in ofile.NBEST [default 300] -units : write units in ofile.UNITS [default 0] -threads i : use i threads [default 1] -verbose : verbose output in ofile.VERBOSE [default 0] -help : this help