In the previous recipe, we flattened a deep Tree by only keeping the lowest level subtrees. In this recipe, we'll keep only the highest level subtrees instead.
We'll be using the first parsed sentence from the treebank corpus as our example. Recall from the previous recipe that the sentence Tree looks like this:
The shallow_tree() function defined in transforms.py eliminates all the nested subtrees, keeping only the top subtree labels:
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)Using it on the first parsed sentence in treebank results in a Tree with only two subtrees:
>>> from transforms import shallow_tree
>>> shallow_tree(treebank.parsed_sents()[0])
Tree('S', [Tree('NP-SBJ', [('Pierre', 'NNP'), ('Vinken', 'NNP'), (',', ','), ('61', 'CD'), (...