
# 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
```
{"library_name": "spacy", "metrics": ["accuracy"], "pipeline_tag": "token-classification"}
spacy token-classification region:us
TAGS
#spacy #token-classification #region-us 


# NER for Early New High German (Frühneuhochdeutsch)
Based on the SpaCy German model and trained on letters from the Bullinger collection

# How to use


# NER for Early New High German (Frühneuhochdeutsch)
Based on the SpaCy German model and trained on letters from the Bullinger collection # How to use
TAGS
#spacy #token-classification #region-us 
 # NER for Early New High German (Frühneuhochdeutsch)
Based on the SpaCy German model and trained on letters from the Bullinger collection # How to use
TAGS
#spacy #token-classification #region-us 
# NER for Early New High German (Frühneuhochdeutsch)
Based on the SpaCy German model and trained on letters from the Bullinger collection# How to use