Sadeque, Farig YousufFarhan, NiloyJoy, Saman SarkerMannan, Tafseer Binte2023-12-072023-12-0720232023-05ID 23341028ID 20101114ID 20101256http://hdl.handle.net/10361/21935Cataloged from PDF version of thesis.Includes bibliographical references (pages 65-66).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.Named Entity Recognition (NER) is a sub-task of Natural Language Processing (NLP) that distinguishes entities from unorganized text into predefined categorization. In recent years, a lot of Bangla NLP subtasks have received quite a lot of attention; but Named Entity Recognition in Bangla still lags behind. In this thesis, we explored the existing state of research in Bangla Named Entity Recognition. We tried to figure out the limitations that current techniques and datasets face, and we would like to address these limitations in our research. Additionally, we developed a Gazetteer that has the ability to significantly boost the performance of NER. We also proposed a new NER solution by taking advantage of state-of-the-art NLP tools that outperform conventional techniques.66 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.NERNLPTransformersBERTGazetteerNatural language processing (Computer science)Artificial intelligenceThesis