Drawing a flatten NLTK Parse Tree with NP chunks

Question

I want to analyze sentences with NLTK and display their chunks as a tree. NLTK offers the method tree.draw() to draw a tree. This following code draws a tree for the sentence "the little yellow dog barked at the cat" :

import nltk 
sentence = [("the", "DT"), ("little", "JJ"), ("yellow", "JJ"), ("dog", "NN"), ("barked","VBD"), ("at", "IN"), ("the", "DT"), ("cat", "NN")]

pattern = "NP: {<DT>?<JJ>*<NN>}"
NPChunker = nltk.RegexpParser(pattern) 
result = NPChunker.parse(sentence)
result.draw()

The result is this tree:

How do i get a tree with one more level like this?

Answer 1

You need to "level up" your non-NP words, here's a hack:

import nltk 
sentence = [("the", "DT"), ("little", "JJ"), ("yellow", "JJ"), ("dog", "NN"), ("barked","VBD"), ("at", "IN"), ("the", "DT"), ("cat", "NN")]

pattern = """NP: {<DT>?<JJ>*<NN>}
VBD: {<VBD>}
IN: {<IN>}"""
NPChunker = nltk.RegexpParser(pattern) 
result = NPChunker.parse(sentence)
result.draw()

[out]:

---

Answer 2

I know it's little too late to answer. But here is how I've done it. The idea is you need to convert your sentence into a tree.

import nltk
sentence = list(map(lambda sent: Tree(sent[1], children=[sent[0]]), sentence))

Then you can do the chunking afterwards.

NPChunker = nltk.RegexpParser(pattern) 
result = NPChunker.parse(sentence)
result.draw()

Here's my result Tree