MEANT 2.0: Accurate semantic MT evaluation for any output language

  title={MEANT 2.0: Accurate semantic MT evaluation for any output language},
  author={Chi-kiu Lo},
We describe a new version of MEANT, which participated in the metrics task of the Second Conference on Machine Translation (WMT 2017). MEANT 2.0 uses idfweighted distributional ngram accuracy to determine the phrasal similarity of semantic role fillers and yields better correlations with human judgments of translation quality than earlier versions. The improved phrasal similarity enables a subversion of MEANT to accurately evaluate translation adequacy for any output language, even languages… CONTINUE READING


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