Bangla natural language inference

Abstract

Natural Language Inference (NLI) plays a vital role in our interpretation of textual data. Understanding texts is often difficult due to the logical and contextual motivations behind them. However, with the help of a text inference model, we can decode it. Our focus will be on Bengali Language Text inference, and we believe it will be useful in understanding the meaning of texts. In this thesis, we will introduce a high-quality Bangla Natural Language Inference dataset. We will also develop a benchmark model that will be able to effectively comprehend the complex semantic and logical relations among texts. The model will use complex deep-learning techniques to draw more meaningful conclusions from the texts. The research topic proposes many benefits, e.g., creating machines that will implement this model to create an effective question-answering system, an information retrieval system, sentiment analysis, and a decision maker.