Human language is laden with intricacies, and it is obvious that one form of annotation won’t be sufficient to cover it. Also, text annotation is use-case-specific and lets developers prepare project-centric models, with relevant info. The highest quality of text annotation lets the machine catch the finer nuances of the language and respond better to user queries. Text annotation, therefore, shows up as a path-breaking technology in this regard, where annotators accurately tag files and content with metadata. Text datasets, even if made available in large volumes, aren’t expected to do any good to these models as they won’t understand the meaning, context, and nuances in the first place. But with such an insane level of competition around, enterprises developing these autonomous resources must deploy state-of-art concepts or rather a text datasets to make them accurate, responsive, and proactive.Īnyways, it isn’t just about the datasets anymore. Why is Text Annotation Important?Ĭhatbots, voice assistants, and machine translators are steadily coming of age. Text annotation should never be confused with text data collection as the latter is simply a process to collect and declutter datasets, while an annotation is a more deep-seated and resource-intensive process that concerns labelling. This is where text annotation comes into play, which ensures that NLP models get relevant training data to learn from. At least not in the formative stage when the predictive model hasn’t been developed in the first place. But machines cannot hear and read to learn. It comprises semantics, i.e., phrasal and text-based elements and sentiments, with a focus on positive, negative, and neutral tones.

Human language isn’t all that simple for machines to understand. Text annotation, therefore, trains NLP or Natural Language Processing models, by making large volumes of data or rather textual datasets, usable enough and understandable to the algorithms. Once these resources are tagged or labelled, they become understandable and can be deployed by the machine learning algorithms to train the models to perfection. In simple words, text annotation is all about labelling specific documents, digital files, and even the associated content. Have you ever seen Google Translate discerning text snippets and converting them to English? If yes, then you are in luck you have already experienced the benefit of text annotation, in real-time.

Text annotation meaning