  Grammatical tense and mood are important linguistic phenomena to consider in
natural language processing (NLP) research. We consider the correspondence
between English and German tense and mood in translation. Human translators do
not find this correspondence easy, and as we will show through careful
analysis, there are no simplistic ways to map tense and mood from one language
to another. Our observations about the challenges of human translation of tense
and mood have important implications for multilingual NLP. Of particular
importance is the challenge of modeling tense and mood in rule-based,
phrase-based statistical and neural machine translation.
