Text annotation aids in the comprehension of text data by machine learning models. Text annotation is frequently used in workflows for entity recognition, classification, part-of-speech tagging, sentiment and intent analysis, and other related tasks. In the text annotation process, the project standards are followed to parse the data into the necessary categories, such as phrases, sentences, and keywords. The annotated datasets teach computers how to effectively converse in human language. Text annotation has numerous applications, including the generation of training data for chatbots, the development of question-answering systems, the enhancement of reading comprehension skills in students, the ease of translating text between languages, and much more. Additionally, text annotation and image annotation can be coupled to train multimodal