Named Entity-Aware Abstractive Text Summarization for Hindi Language

Abstract

In this study, we introduce a novel approach to text summarization, specifically tailored for the Hindi language, titled Named Entity-Aware Abstractive Text Summarization (NEA-ATS). Our methodology uniquely integrates Named Entity Recognition with advanced pretrained language models, focusing on critical entities such as individuals, locations, and organizations. We use our proposed methodology along with the pretrained models to work on the ILSUM task to provide summaries for Hindi news articles. We secured the first rank for the Hindi summarization task. Our comprehensive evaluation offers valuable insights into enhancing the NEA-ATS methodology in the future, along with determining efficient methods and model for Hindi summarization. © 2023 Copyright for this paper by its authors.