• Version --> v2019.4.3
  • This programme is an extension to previous version and has an patch update.
  • When it comes to assigning a tag to an ambigiuous word (words with multiple tags in the package) the Tagger achieves accuracy of 60-70% .


In Natural Language Processing, Part-of-Speech (POS) tagging is the process of marking up a word in a text sentence of a natural language as corresponding to a particular part of speech, in accordance with its definition and context. This is a Mathematical (Stochastic) Model based Part-of-Speech (POS) Tagger for Nepali developed under the project funded by Department of Science and Technology, Ministry of Human Resource Development. The Software is implemented in Python. The Tagger achieves accuracy of 100% for the non-ambiguious words available in the software package. However, it is assigning the most probable tags for the words that are not available in the package.