Why Text Annotation is Essential for NLP Model Accuracy Text annotation is crucial for training supervised NLP models by providing labeled data that helps algorithms learn patterns and relationships in text. Without annotation, NLP models struggle to process raw data effectively. Different annotation types serve specific NLP tasks, including Named Entity Recognition (NER), sentiment annotation, POS tagging, text classification, and relation extraction. Read more : https://www.fbspl.com/blogs/why-text-annotation-is-the-backbone-of-supervised-nlp-models