Simple chunk tagger implementation for the English language
A chunking model is trained with a corpus containing almost 9,000 English sentences.

Model (mini model) in the repo is trained using mini data which contains only almost 100 English sentences.
Therefore, it does not perform well enough.

I encourage you to train a new model on your own using the corpus in data/ directory.
My training lasted almost 14 minutes on a device with 3,1 GHz Intel Core i7 processor.

$python3 chunk.py input-sentence

$cd src
$python3 chunk.py "This is the strangest life I've ever known."
-> Chunker is loaded.
-> [('This', 'B-NP'), ('is', 'B-VP'), ('the', 'B-NP'), ('strangest', 'I-NP'), ('life', 'I-NP'), ('I', 'B-NP'), ("'ve", 'B-VP'), ('ever', 'I-VP'), ('known', 'I-VP'), ('.', 'O')]

P.S. Above example is tested with a model trained on corpus in data/ directory(with almost 9,000 English sentences).

This is the strangest life I've ever known.
Jim Morrison