Chunking example using FlairNLP https://github.com/flairNLP/flair/

flair_chunking_example.py

from flair.data import Sentence
from flair.models import SequenceTagger
import sys

class FlairChunker():
    def __init__(self):
        self.chunker = SequenceTagger.load('chunk')

    def get_chunk_spans(self, s):
        sentence = Sentence(s)
        self.chunker.predict(sentence)
        spans = sentence.get_spans('np')
        return spans

def main():
    #sentence_file = sys.argv[1]
    #sentences = open(sentence_file, 'r').readlines()
    sentences = ["The cat sat on the mat the dog chewed ."]
    flairchunker = FlairChunker()
    for s in sentences:
        print('\n Input sentence: ', s)
        spans = flairchunker.get_chunk_spans(s)
        for entity in spans:
            print(entity)

if __name__ == "__main__":
    main()

Output:
Input sentence: The cat sat on the mat the dog chewed .
Span [1,2]: "The cat" [− Labels: NP (0.9999)]
Span [3]: "sat" [− Labels: VP (1.0)]
Span [4]: "on" [− Labels: PP (0.9956)]
Span [5,6]: "the mat" [− Labels: NP (0.9998)]
Span [7,8]: "the dog" [− Labels: NP (0.9985)]
Span [9]: "chewed" [− Labels: VP (1.0)]