initial model commit

README.md

@@ -66,21 +66,20 @@ print(sentence)
 # print predicted NER spans
 print('The following NER tags are found:')
 # iterate over entities and print
-for entity in sentence.get_spans('upos'):
+for entity in sentence.get_spans('pos'):
     print(entity)
 
 ```
 
 This yields the following output:
 ```
-Span [1]: "I"   [− Labels: PRP (1.0)]
-Span [2]: "love"   [− Labels: VBP (1.0)]
-Span [3]: "Berlin"   [− Labels: NNP (0.9999)]
-Span [4]: "."   [− Labels: . (1.0)]
-
+Span [1]: "I"   [− Labels: PRON (0.9996)]
+Span [2]: "love"   [− Labels: VERB (1.0)]
+Span [3]: "Berlin"   [− Labels: PROPN (0.9986)]
+Span [4]: "."   [− Labels: PUNCT (1.0)]
 ```
 
-So, the word "*I*" is labeled as a **pronoun** (PRP),  "*love*" is labeled as a **verb** (VBP) and "*Berlin*" is labeled as a **proper noun** (NNP) in the sentence "*TheI love Berlin*". 
+So, the word "*I*" is labeled as a **pronoun** (PRON),  "*love*" is labeled as a **verb** (VERB) and "*Berlin*" is labeled as a **proper noun** (PROPN) in the sentence "*TheI love Berlin*". 
 
 
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