Update README.md

README.md

@@ -70,29 +70,28 @@ tagger = SequenceTagger.load("flair/upos-multi")
 # make example sentence
 sentence = Sentence("Ich liebe Berlin, as they say. ")
 
-# predict NER tags
+# predict POS 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('pos'):
-    print(entity)
+# iterate over tokens and print the predicted POS label
+print("The following POS tags are found:")
+for token in sentence:
+    print(token.get_label("upos"))
 ```
 
 This yields the following output:
 ```
-Span [1]: "Ich"   [− Labels: PRON (0.9999)]
-Span [2]: "liebe"   [− Labels: VERB (0.9999)]
-Span [3]: "Berlin"   [− Labels: PROPN (0.9997)]
-Span [4]: ","   [− Labels: PUNCT (1.0)]
-Span [5]: "as"   [− Labels: SCONJ (0.9991)]
-Span [6]: "they"   [− Labels: PRON (0.9998)]
-Span [7]: "say"   [− Labels: VERB (0.9998)]
-Span [8]: "."   [− Labels: PUNCT (1.0)]
+Token[0]: "Ich" → PRON (0.9999)
+Token[1]: "liebe" → VERB (0.9999)
+Token[2]: "Berlin" → PROPN (0.9997)
+Token[3]: "," → PUNCT (1.0)
+Token[4]: "as" → SCONJ (0.9991)
+Token[5]: "they" → PRON (0.9998)
+Token[6]: "say" → VERB (0.9998)
+Token[7]: "." → PUNCT (1.0)
 ```
 
 So, the words "*Ich*" and "*they*" are labeled as **pronouns** (PRON), while "*liebe*" and "*say*" are labeled as **verbs** (VERB) in the multilingual sentence "*Ich liebe Berlin, as they say*".