parl-german-ner-bt is trained on German parliamentary speeches to tag a sequence with fine-grained named entities (e.g., geo-political entities, persons, organizations). The NER tag inventory is adapted from the
OntoNotes NER inventory.
See
schlenker/parl-german-ner which is trained on a mix of news data and parliamentary speeches.
Models were trained and evaluated on 267 manually annotated parliamentary speeches (resulting in 10,564 annotated entities).
Please, refer to our GitHub repo for detailed instructions on the required input format and how to run the model.
