WMT2017 German-English machine translation challenge for news
Translate news articles from German into English.
This is WMT2017 news challenge reformatted as a Gonito.net challenge, all the data were taken from http://www.statmt.org/wmt17/translation-task.html.
BLEU is used as the evaluation metric.
README.md— this file
config.txt— configuration file
train/— directory with training data
train/commoncrawl.tsv.xz— Common Crawl parallel corpus
train/europarl-v7.tsv.xz— Europarl parallel corpus
train/news-commentary-v12.tsv.xz— News Commentary parallel corpus
train/rapid2016.tsv.xz— Rapid corpus of EU press releases
dev-0/— directory with dev (test) data (WMT2015 test set)
dev-0/in.tsv— German input text for the dev set
dev-0/expected.tsv— English reference translation for the dev set
dev-1/— directory with dev (test) data (WMT2016 test set)
dev-1/in.tsv— German input text for the dev set
dev-1/expected.tsv— English reference translation for the dev set
test-A— directory with test data
test-A/in.tsv— German input data for the test set (WMT2017 test set)
test-A/expected.tsv— English reference translation for the test set
All training sets were compressed with xz, use
xzcat to decompress:
$ xzcat train/*.tsv.xz | ...
The pairs where German or English side is empty were removed from the training sets.
$ xzcat train/*.tsv.xz | wc 5906167 247901483 1680105853 $ xzcat train/*.tsv.xz | cut -f 1 | wc -m 876313942 $ xzcat train/*.tsv.xz | cut -f 2 | wc -m 787047585
Reference English translations in the dev and test sets were tokenised using Moses MT tokeniser (without HTML escaping).
Monolingual data was not included here.