This article provides a detailed overview of Named Entity Recognition (NER), a key aspect of Natural Language Processing (NLP) that identifies and classifies named entities in text. The author explores various NER methodologies, from traditional rule-based strategies to advanced AI techniques like BERT integrated with LSTM and CNN. The article also delves into domain-specific NER models for sectors like finance, legal, and healthcare, and discusses the role of technologies like Optical Character Recognition (OCR) in enhancing NER capabilities. The paper also outlines the challenges and future research directions in NER.
Publication date: 25 Sep 2023
Project Page: https://arxiv.org/abs/2309.14084v1
Paper: https://arxiv.org/pdf/2309.14084
