bangla_pos_tagger

POS Tagger for Bangla language based on Conditional Random Fields

Usage

1. Install the module python setup.py install

2. Code import bangla_pos_tagger bangla_pos_tagger.pos_tag(query)

where query is a tokenized words for a given Bangla Sentence.

Observations

• Unigram Based Tagger gives approximately 60-65% accuracy.
• Adding Bigram, and Trigram based taggers following the same increases the accuracy to some extent.
• Adding an affix based tagger, improves the accuracy a bit.

Note: In the "accuracy.txt" file in the analyzed_data directory. Only the relevant results have been added which were giving really good accuracies. The analysis is similar to that of the blog.

Relevant Blog Posts

1. http://streamhacker.com/2008/12/29/how-to-train-a-nltk-chunker/
2. http://streamhacker.com/2008/11/10/part-of-speech-tagging-with-nltk-part-2/
3. http://streamhacker.com/2008/12/03/part-of-speech-tagging-with-nltk-part-3/
4. http://streamhacker.com/2010/04/12/pos-tag-nltk-brill-classifier/