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---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- conll2003
inference: false
---
## English NER in Flair (default model)
This is the standard 4-class NER model for English that ships with Flair.
Classes:
PER (person name)
LOC (location name)
ORG (organization name)
MISC (other names)
### Demo: How to use in Flair
```python
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("flair/ner-english")
# make example sentence
sentence = Sentence("George Washington went to Washington")
# predict NER tags
tagger.predict(sentence)
# print sentence
print(sentence)
# print predicted NER spans
print('The following NER tags are found:')
# iterate over entities and print
for entity in sentence.get_spans('ner'):
print(entity)
```
yields the following output:
> `Span [1,2]: "George Washington" [− Labels: PER (0.9968)]
Span [5]: "Washington" [− Labels: LOC (0.9994)]`
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