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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 btagger=bangla_pos_tagger.BanglaTagger()

    #Query is an array of Bangla words btagger.pos_tag(query)

    #term is a single Bengali Term btagger.get_tag(term)

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.

Data Sets

Dataset "bangla.pos" as comes packaged with NLTK Dataset "nltr" from nltr.org Dataset "msr" containing files [1-9,e1,e2].xml as described here - http://www.ldc.upenn.edu/Catalog/catalogEntry.jsp?catalogId=LDC2010T16 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/