initial commit

README.md

@@ -13,7 +13,7 @@ inference: false
 
 This is the large 4-class NER model for German that ships with [Flair](https://github.com/flairNLP/flair/).
 
-F1-Score: **94,36** (CoNLL-03)
+F1-Score: **92,31** (CoNLL-03 German revised)
 
 **! This model only works with Flair version 0.8 (will be released in the next few days) !**
 
@@ -42,7 +42,7 @@ from flair.models import SequenceTagger
 tagger = SequenceTagger.load("flair/ner-german-large")
 
 # make example sentence
-sentence = Sentence("George Washington went to Washington")
+sentence = Sentence("George Washington ging nach Washington")
 
 # predict NER tags
 tagger.predict(sentence)
@@ -64,7 +64,7 @@ Span [1,2]: "George Washington"   [− Labels: PER (1.0)]
 Span [5]: "Washington"   [− Labels: LOC (1.0)]
 ```
 
-So, the entities "*George Washington*" (labeled as a **person**) and "*Washington*" (labeled as a **location**) are found in the sentence "*George Washington went to Washington*". 
+So, the entities "*George Washington*" (labeled as a **person**) and "*Washington*" (labeled as a **location**) are found in the sentence "*George Washington ging nach Washington*". 
 
 
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