Rajspeaks / Machine-Learning-approach-to-Bengali-POS-Tagging-using-NLTK

Bengali POS Tagging using Indian Corpus through NLTK. A sample testing to apply POS Tagging under the supervision of Prof. Sandipan Ganguly, HIT-K.

Machine Learning approach to Bengali POS Tagging using NLTK on Indian-Corpus

Indian corpus is a collection of these Indian Languages: Bengali, Hindi, Marathi, and Telugu language data. NLTK is Natural Language Toolkit Library.

Methodology

• Here I have imported NLTK(Natural Language Tool Kit).
• Imported indian corpus from NLTK.
• Stored that Indian Corpus into 'bangla.pos'.
• 'bangla.pos' has been stored in a variable 'tagged_set'.
• Stored the bengali sentences from bengali corpus into 'word_set' variable.
• Using for loop to count the number of sentences, present in that corpus.

Tools & Library requirements:

• Google Colab/Jupyter
• Language: Python
• NLTK Library

Mentor:

Prof. Sandipan Ganguly

Developer:

Rajdeep Das

Reference:

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