Towards Robust Named Entity Recognition for Historic German

Based on our paper we release a new model trained on the LFT dataset.

Note: We use BPEmbeddings instead of the combination of Wikipedia, Common Crawl and character embeddings (as used in the paper), so save space and training/inferencing time.

Results

Dataset \ Run	Run 1	Run 2	Run 3†	Avg.
Development	76.32	76.13	76.36	76.27
Test	77.07	77.35	77.20	77.21

Paper reported an averaged F1-score of 77.51.

† denotes that this model is selected for upload.