It is essentially a translation by analogy and can be viewed as an implementation of a case-based reasoning approach to machine learning.
[1] He pointed out that it is especially adapted to translation between two totally different languages, such as English and Japanese.
Example-based machine translation systems are trained from bilingual parallel corpora containing sentence pairs like the example shown in the table above.
For example, if we have been trained using some text containing the sentences: President Kennedy was shot dead during the parade.
Example-based machine translation is best suited for sub-language phenomena like phrasal verbs.