Update README.md

README.md

@@ -11,9 +11,10 @@ inference: false
 
 ## English NER in Flair (default model)
 
-This is the standard 4-class NER model for English that ships with Flair, trained on CoNLL-03. 
+This is the standard 4-class NER model for English that ships with [Flair](https://github.com/flairNLP/flair/).
 
-F1-Score: **92,98**
+- F1-Score: **92,98**
+- Trained on: CoNLL-03 
 
 Predicts 4 tags:
 
@@ -24,10 +25,10 @@ Predicts 4 tags:
 | ORG         | organization name | 
 | MISC         | other name | 
 
-
-
 ### Demo: How to use in Flair
 
+Requires: **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`)
+
 ```python
 from flair.data import Sentence
 from flair.models import SequenceTagger
@@ -52,12 +53,14 @@ for entity in sentence.get_spans('ner'):
 
 ```
 
-yields the following output:
+This yields the following output:
 ```
 Span [1,2]: "George Washington"   [− Labels: PER (0.9968)]
 Span [5]: "Washington"   [− Labels: LOC (0.9994)]
 ```
 
+Indicating that the entities "George Washington" (labeled as a person) and "Washington" (labeled as a location) are found in the sentence "George Washington went to Washington". 
+
 
 ### Training: Script to train this model