Read about TNT

python3 main.py (the input sentence must be in Nepali unicode font) (any other fonts/languages input will be wrongly tagged)

Remove the dictionary/ folder and its components first after cloning the project. It contains the trained dataset trained form a sample put in the folder tagset/cs The training dataset format/example is given in tagset/cs folder. It is a .xml file The sample was obtained from database of NELRAREC.

For full dataset contact NELRAREC and Bhasa Sansar authorities. The obtaines files are to be put into the tagset/cs drectories. OR as per you want so as along as you give the correct path for the dataset folder in the file get_data.py NEPALI_CORPUS_DIR = './tagset/cs' (currently) or NEPALI_CORPUS_DIR = '(the path for the dataset folder)'

(Important: Delete the dictionary/ folder and its components. As of now it has the trained set of the current sample of tagset/cs file in the repo) (The dictionary/ folder will itself be created later on) Run in command line: python main.py (The dictionary folder will be created automatically) (If you have a new dataset, delete the previously created dictionary/ folder)

python3 test.py (You can chose a specific tagged file form the dataset to test)

pip install -r requirements.txt

python3 train_tagger.py (This is still on todo list . It is for training the dataset using the given HMM algorithn(tnt_tagger) defined in nltk package)

A brief description about Neplai POS and tags definition as given by NELRAREC is given in the .pdf document.