As you've seen in previous recipes, parse trees often have a variety of Tree label types that are not present in chunk trees. If you want to use parse trees to train a chunker, then you'll probably want to reduce this variety by converting some of these tree labels to more common label types.
First, we have to decide which Tree labels need to be converted. Let's take a look at that first Tree again:
Immediately, you can see that there are two alternative NP subtrees: NP-SBJ and NP-TMP. Let's convert both of those to NP. The mapping will be as follows:
|
Original Label |
New Label |
|---|---|
|
NP-SBJ |
NP |
|
NP-TMP |
NP |
In transforms.py is the function convert_tree_labels(). It takes two arguments: the Tree to convert and a label conversion mapping. It returns a new Tree with all matching labels replaced based on the values in the mapping:
from nltk.tree import Tree
def convert_tree_labels(tree, mapping):
children = []
for t in tree:
if isinstance(t...
