Both show an [proved relationship between model score and F-:asure.

Digging deeper, we compared parser model score against Viterbi F—score and oracle F-score at a va-

The labels for leaves will be words, and will be important in defining strings and language model scores for those strings.

For each 12 E VL, define av = maxpm3(p)=v Mp), where MP) = (100109): 02(19):0309))—/\1(01(P))—/\2(v2(19))—Zsepl(p) — 25610209) Here h is a function that computes language model scores , and the other terms involve Lagrange mulipliers.

Informally, the first decoding algorithm incorporates the weights and hard constraints on translations from the synchronous grammar, while the second decoding algorithm is used to integrate language model scores .

We compare our method to cube pruning (Chiang, 2007), and find that our method gives improved model scores on a significant number of examples.

In the simple algorithm, the first step was to predict the previous leaf for each leaf 21, under a score that combined a language model score with a Lagrange multiplier score (i.e., compute arg Inan 6(711, 21) where 6011,21) = 6011,11) + In this section we describe an algorithm that for each leaf 21 again predicts the previous leaf, but in addition predicts the full path back to that leaf.