Specifically, we leverage recent advances in data-efficient learning for low-resource languages, proposing the following "recipe" for bootstrapping low-resource entity recognizers: First, we use cross-lingual transfer learning (Yarowsky et al., 2001;Ammar et al., 2016), which applies a model trained on another language to low-resource languages, to provide a good preliminary model to start the bootstrapping process.
we use the model of Xie et al.