There is no denying that text annotation is a widely used type as 70 per cent of organizations surveyed in the ML report stated that they are highly dependent on text. Text annotation involves a process of utilizing metadata tags for highlighting sentences, phrases or keywords to impart machines on how to identify and comprehend human emotions accurately through words. The feelings that are highlighted are used to train data for the machines to ensure it processes efficiently and also engage well with digital text communication and human language naturally.
Accuracy plays a crucial role in text annotation because inaccurate annotations may lead to misspelt words or misinterpretation. As a result, it becomes tough to understand phrases or words in a particular context. Machines need to understand every phrase of a specific statement or question based on the way humans interact or speak through the internet.
For instance, when a user phrases a sentence or a question in a manner that the machine may not be familiar with, it becomes almost impossible for the machine to get to the ending point and obtain a solution. Therefore, if the text annotation is accurate then the machine can easily perform huge tasks that consume a whole lot of time. This way, customers can have a greater experience and also companies can meet their objectives and make the best use of human resources.