Inspired by example-based machine translation model (Nagao, 1984;Sato and Nagao, 1990), we assume that certain mappings in the training set are identical with the transformation of the input NE.
thus we materialize the semantic information as a set of C2E mappings coming from the training set the semantic-specific translation model incorporates semantic information by finding out the most likely mappings coming from the training set to capture the semantic structure.