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An n-gram is simply a grouping of tokens/words. A unigram (1-gram) would consist of a single word. A bigram (2-gram) consists of two consecutive words: The reference is a human-made best-case output — so for automated summarization is ...BLEU* (C2) = 5/5 = 1. We achieved a perfect score with a non-sense translation, there’s something we need to correct on our metric. It doesn’t make sense to consider the word “The” five ...BLEU and BERT scores of the pocket sentences, similarity to the first sentence BERTScore (Updated on 06.11.2019) This is an update as I recently found an article with the idea to use BERT for evaluating Machine Translation systems [4]. 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