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Grammatical tense and mood are important linguistic phenomena to consider innatural language processing (NLP) research. We consider the correspondencebetween English and German tense and mood in translation. Human translators donot find this correspondence easy, and as we will show through carefulanalysis, there are no simplistic ways to map tense and mood from one languageto another. Our observations about the challenges of human translation of tenseand mood have important implications for multilingual NLP. Of particularimportance is the challenge of modeling tense and mood in rule-based,phrase-based statistical and neural machine translation.

Pragmatic information in translation: a corpus-based study of tense and mood in English and German