Yet languages also differ in many ways, and an understanding of what causes such translation divergences will help us build better MT models. We often distin-translation divergence guish the idiosyncratic and lexical differences that must be dealt with one by one (the word for "dog" differs wildly from language to language), from systematic differences that we can model in a general way (many languages put the verb before the direct object; others put the verb after the direct object). The study of these systematic cross-linguistic similarities and differences is called linguistic typology. This typology section sketches some typological facts that impact machine translation; the interested reader should also look into WALS, the World Atlas of Language Structures, which gives many typological facts about languages (Dryer and Haspelmath, 2013).