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https://github.com/moses-smt/mosesdecoder.git
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a25193cc5d
This is lint reported by the new lint-checking functionality in beautify.py. (We can change to a different lint checker if we have a better one, but it would probably still flag these same problems.) Lint checking can help a lot, but only if we get the lint under control. |
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.. | ||
perllib | ||
smtgui | ||
bootstrap-hypothesis-difference-significance.pl | ||
extract-target-trees.py | ||
nontranslated_words.pl | ||
oov.pl | ||
README | ||
sentence-by-sentence.pl | ||
sg2dot.perl | ||
show-phrases-used.pl | ||
suspicious_tokenization.pl | ||
weight-scan-summarize.sh | ||
weight-scan.pl |
Put any scripts useful for human analysis of MT output here. sentence-by-sentence.pl [EVH]: show comparison of sentences in reference translation(s)/system output(s)/(truth) in colorful format -- show all sentences given, with non-matching words in the system output marked, BLEU scores given by sentence, and matching n-grams shown in a table -- requires all input files be utf8-encoded (you can convert a file with `cat FILE | perl -n -e 'binmode(STDOUT, ":utf8"); print;' > FILE.utf8`) show-phrases-used.pl [EVH]: draw colorful diagram of which source phrases map to which target phrases -- requires the Perl GD module, which in turn requires that gd be installed and in LD_LIBRARY_PATH -- show average length of source phrases used for each sentence and overall -- command-line options -r for reference and -s for source; lone filenames are taken to be system outputs