Before revision:  Our results show that explicitly modeling morphological boundaries consistently leads to improved NER performance, and that a novel hybrid architecture that we propose , in which NER precedes and prunes the morphological decomposition(MD) space , greatly outperforms the standard pipeline approach, on both Hebrew NER and Hebrew MD in realistic scenarios .
After revision:  Our results show that explicitly modeling morphological boundaries consistently leads to improved NER performance, and that a novel hybrid architecture that we propose , in which NER precedes and prunes the morphological decomposition(MD) space , greatly outperforms the standard pipeline approach, on both Hebrew NER and Hebrew morphological decomposition tasks .