Therefore , in order to be able to incorporate long-range dependencies in our models , we chose to adopt a re-ranking approach ( Collins 2000 ) , which selects from likely assignments generated by a model which makes stronger independence assumptions .
discriminative reranking for natural language parsing
Michael Collins
Training a model which has such a huge number of classes is infeasible if the model does not factorize due to strong independence assumptions . Therefore , in order to be able to incorporate long-range dependencies in our models , we chose to adopt a re-ranking approach ( Collins 2000 ) , which selects from likely assignments generated by a model which makes stronger independence assumptions . We utilize the top n assignments of our local semantic role labeling model PSRL to generate likely assignments .
Therefore , in order to be able to incorporate long-range dependencies in our models , we chose to adopt a re-ranking approach ( @@CITATION ) , which selects from likely assignments generated by a model which makes stronger independence assumptions .