| | --- |
| | library_name: spacy |
| | metrics: |
| | - accuracy |
| | pipeline_tag: token-classification |
| | --- |
| | |
| | # NER for Early New High German (Frühneuhochdeutsch) |
| | Based on the SpaCy German model and trained on letters from the [Bullinger collection](http://www.bullinger-digital.ch/) |
| |
|
| | # How to use |
| |
|
| | ```python |
| | import spacy |
| | nlp = spacy.load('./enhg-ner') |
| | doc = nlp('Ich hab euch uff gestert ouch by ainem mennlin von Strasburg geschriben mitt ainem brieff gen Bern gehörig.') |
| | for ent in doc.ents: |
| | print(ent.text, ent.label_) |
| | |
| | # Output: |
| | # Strasburg GEO |
| | # Bern GEO |
| | ``` |
