Sharing Network Parameters for Crosslingual Named Entity Recognition

Understand

Most state of the art approaches for Named Entity Recognition rely on hand crafted features and annotated corpora.

• Recently Neural network based models have been proposed which do not require handcrafted features but still require annotated corpora.
• However, such annotated corpora may not be available for many languages.
• In this paper, we propose a neural network based model which allows sharing the decoder as well as word and character level parameters between two languages thereby allowing a resource fortunate language to aid a resource deprived language.