We will choose our universal parameter values by minimizing an estimate of their expected loss, where L train is a collection of training languages (ideally drawn IID from the distribution D of possible human languages) for which some syntactic information is available.
each training language has a treebank (x ( ) , y ( ) ), where x ( ) is a collection of POS-tagged sentences whose correct dependency trees are given by y ( ) .