Towards Robust Named Entity Recognition for Historic German

Based on our paper we release a new model trained on the ONB 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 86.69 86.13 87.18 86.67
Test 85.27 86.05 85.75† 85.69

Paper reported an averaged F1-score of 85.31.

† denotes that this model is selected for upload.

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