If we assume that the classifier returns a score, score(S i = s i ), corresponding to the likelihood of seeing label s i for phrase S i , then, given a sentence, the unaltered inference task that is solved by our system maximizes the score of the phrase, score(S 1:M = s 1:M ), (1) The second step for phrase identification is eliminating labelings using global constraints derived from linguistic information and structural considerations.
we limit the solution space through the used of a filter function, F , that eliminates many phrase labelings from consideration.