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.

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