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NLP | Creating Shallow Tree

  • Last Updated : 26 Feb, 2019

Prerequisite: Flattening Deep Tree

We have flattened a Deep Tree by only keeping the lowest level subtrees. But here we can keep the highest level subtrees instead.

Code #1 : Lets’ understand shallow_tree()




from nltk.tree import Tree
  
def shallow_tree(tree):
        children = []
          
    for t in tree:
        if t.height() < 3:
            children.extend(t.pos())
    else:
        children.append(Tree(t.label(), t.pos()))
          
    return Tree(tree.label(), children)

 

Code #2 : Evaluating






from transforms import shallow_tree
from nltk.corpus import treebank
   
print ("Deep Tree : \n", treebank.parsed_sents()[0])
  
print ("\nShallow Tree : \n", shallow_tree(treebank.parsed_sents()[0]) )

Output :

Deep Tree : 
 (S
  (NP-SBJ
    (NP (NNP Pierre) (NNP Vinken))
    (,, )
    (ADJP (NP (CD 61) (NNS years)) (JJ old))
    (,, ))
  (VP
    (MD will)
    (VP
      (VB join)
      (NP (DT the) (NN board))
      (PP-CLR (IN as) (NP (DT a) (JJ nonexecutive) (NN director)))
      (NP-TMP (NNP Nov.) (CD 29))))
  (. .))

Shallow Tree :
Tree('S', [Tree('NP-SBJ', [('Pierre', 'NNP'), ('Vinken', 'NNP'), (', ', ', '), 
('61', 'CD'), ('years', 'NNS'), ('old', 'JJ'), (', ', ', ')]),
Tree('VP', [('will', 'MD'), ('join', 'VB'), ('the', 'DT'), ('board', 'NN'), 
('as', 'IN'), ('a', 'DT'), ('nonexecutive', 'JJ'), ('director', 'NN'), 
('Nov.', 'NNP'), ('29', 'CD')]), ('.', '.')])

How it works ?

  • shallow_tree() function creates new child trees by iterating over each of the top-level subtrees.
  • The subtree is replaced by a list of its part-of-speech tagged children, if the height() of a subtree is less than 3.
  • If children of a tree are the part-of-speech tagged leaves, the All other subtrees are replaced by a new Tree.
  • Thus, eliminates all the nested subtrees while still retaining the top-level subtrees.

Code #3 : height




print ("height of tree : "
       treebank.parsed_sents()[0].height())
  
print ("\nheight of shallow tree : "
       shallow_tree(treebank.parsed_sents()[0]).height())

Output :

height of tree : 7

height of shallow tree :3

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