Add examples and description in docs

docs/docs/gettingstarted/quickstart.md

@@ -40,17 +40,21 @@ nlp = load_spacy_model()
 
 # Parse the text using the spaCy model 
 # it creates a spaCy Doc object
-doc = nlp("Jeg er en sætning, der skal analyseres")
+doc = nlp("Niels Henrik David Bohr var en dansk fysiker fra København")
 
 # prepare some pretty printing
-features = ['Text','POS', 'Dep']
+features = ['Text','POS', 'Dep', 'NE']
 head_format ="\033[1m{!s:>11}\033[0m" * (len(features) )
 row_format ="{!s:>11}" * (len(features) )
 
 print(head_format.format(*features))
-# printing for each token in the docs the pos and dep features
+# printing for each token in the docs the pos, dep and entity features
 for token in doc:
-    print(row_format.format(token.text, token.pos_, token.dep_))
+    print(row_format.format(token.text, token.pos_, token.dep_, token.ent_type_))
+
+# printing the list of entities (and their category)
+for ent in doc.ents:
+    print(ent.text, '-', ent.label_)
 
 ```
 
@@ -95,7 +99,7 @@ text = "Jeg er meget glad med DaNLP"
 doc = nlpS(text)
 
 # print the most probable category among 'positiv', 'negativ' or 'neutral'
-print(max(doc.cats))
+print(max(doc.cats, key=doc.cats.get))
 ```
 
 

docs/docs/tasks/pos.md

@@ -1,6 +1,8 @@
 Part of Speech Tagging
 ======================
-This section is concerned with public available Part of Speech (POS) taggers in Danish. 
+This section is concerned with public available Part of Speech (POS) taggers in Danish.
+
+Part-of-speech tagging is the task of classifying words into their part-of-speech, based on both their definition and context. Parts of speech are also known as word classes, which describe the role of the words in sentences relatively to their neighbors (such as verbs and nouns). 
 
 | Model                 | Train Data                                                                | License       | Trained by          | Tags                         | DaNLP |
 |-----------------------|---------------------------------------------------------------------------|---------------|---------------------|------------------------------|-------|