How to do POS tagging using SVM in Python?

Question

I want to do POS tagging using SVM with non-English corpus in Python. It looks like Python does not support tagging using SVM yet (http://www.nltk.org/_modules).

scikit-learn has a SVM module. So I installed scikit-learn and use it in Python but I cannot find any tutorials about POS tagging using SVM.

I really have no clue what to do, any help would be appreciated.

Estrone

Answer 1

Does it have to be an SVM? NTLK has built-in tools to do POS tagging: Categorizing and Tagging Words

If you want to use a custom classifier, look here: http://www.nltk.org/api/nltk.classify.html, Ctrl+F "svm", NTLK provides a wrapper for scikit-learn algorithms called SklearnClassifier. Then take a look here http://www.nltk.org/api/nltk.tag.html, Ctrl+F "classifier", there is a class nltk.tag.sequential.ClassifierBasedPOSTaggerwhich apparently can use wrapped up classifiers from sklearn.

I haven't tried this but it might work.

EDIT: It should work like this:

from nltk.classify import SklearnClassifier
from sklearn.svm import SVC
clf = SklearnClassifier(SVC(),sparse=False)
cpos = nltk.tag.sequential.ClassifierBasedPOSTagger(train=train_sents,classifier_builder
= lambda train_feats: clf.train(train_feats))

The only problem is that sklearn classifiers take numerical features only, so you need to convert yours somehow.

Peashooter

Thanks, hellpanderrr. I tried other tagger (CRF, TBL, HMM,...) and wanted to use SVM. I used this wrapper but still cannot do any POS tagging. – Estrone

With other taggers in Python, you only need training data to train, then you can use tag method and evaluate method. But when I use SVM of scikit-learn or SklearnClassifier, I cannot find any method to train or tag. – Estrone