The contributions provided by incorporating unlabeled data in our hybrid model can be seen by comparison with the performance of the first and third rows in HySOL, namely a 2.64 point F-score and a 2.96 point sentence accuracy gain in the NER experiments and a 0.46 point F-score and a 1.99 point sentence accuracy gain in the Chunking experiments.
we divided the labeled training data into 4/5 for estimating Λ and 1/5 for estimating Γ; one feature type shown in    We evaluated the performance in terms of the F β=1 score, which is the evaluation measure used in CoNLL-2000 and, and sentence accuracy, since all the methods in our experiments optimize sequence loss.