Identifying specific details from text to populate databases and generate summaries using Named Entity Recognition

Abstract

Named Entity Recognition (NER) is a natural language processing (NLP) technique that focuses on identifying and classifying entities within a text. Entities are typically real-world objects that have names, such as people, organizations, locations, dates, percentages, currencies, and more. NER is used to extract structured information from unstructured text data and is an important component of various NLP applications, including question generation, information retrieval, text summarization, and more. Index Terms— Named Entity Recognition (NER), Natural language processing (NLP), text summarization.