• K Neha
• P. Shivani
• M. Indu
• S. Arjun
• Dr.M.V.Vijaya Saradhi

Natural Language Processing domain is mainly used in fields such as Information retrieval and Text mining. These do not have a built-in semantic disambiguate and thus, it has to be performed explicitly. This has been largely performed on sentences in the English language to identify the context of a word in that sentence. This project’s main idea is to implement semantic distinguishing in sentence by giving examples for regional language Telugu. Since, Telugu vocabulary is huge, occurrences of ambiguity is common and this project is aimed at resolving them. To achieve this, a synset is used, which is an interface for the Telugu WordNet. The algorithm used in this project is the Lesk algorithm. It is based on the assumption that the correct meaning or sense of a word is dependent upon the words present in its neighborhood. More specifically, context of a word is determined by comparing the meaning of each sense of the word with the meanings of the neighboring words. This project aims to get the examples for each ambiguous word in the sentence using Lesk algorithm.

Semantic distinguishing , Telugu, Lesk algorithm, WordNet, Python.

"Semantic Distinguishing To Identify The Context Of Words In Telugu Sentences", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.c73-c77, June-2022, Available :http://www.jetir.org/papers/JETIR2206207.pdf

"Semantic Distinguishing To Identify The Context Of Words In Telugu Sentences", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppc73-c77, June-2022, Available at : http://www.jetir.org/papers/JETIR2206207.pdf