AI-Cafe presents: Named Entity Recognition: Using deep-learning approaches for extracting entities

We will briefly introduce the deep-learning approaches that tackle the task of NER, followed by a comparative evaluation between multiple setups of a chosen network architecture. The biggest available datasets for German, CoNLL-2003 and GermEval2014 will be used to train and evaluate the NER models. Finally, we will see how transfer learning can be applied, to improve the performance of pre-trained models in "low-data" settings.

This technology is listed in the AI Assets Catalog.