GenAI for Better NLP Systems III: A Tool That Simplifies Text Annotation

Author(s): Nabanita Roy

Originally published on Towards AI.

This article explores how prompt engineering & LLMs offer a digital, quick, and better annotation approach over manual ones

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Image Source : Author (Inspiration: https://www.dqlabs.ai/blog/what-is-data-quality-management/)

Let’s start with a question for this article, shall we? How do you tell the Machine Learning models the meaning of a particular word, especially when they are quantitatively intelligent and lexically challenged?

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Data annotation plays a crucial role in developing and assessing NLP models with supervised learning, a branch of machine learning that relies on the guidance it receives to train on a set of data points. It involves identifying and labeling text with additional information to specify the role of words or sentences in the given context.

Annotations are widely used in medical research (vast medical terms/jargons in literature), finance and legals (sentiment and other indicators), customer service and chatbots (identify specific keywords and action them), social media, retail and e-commerce and so on. This definitely estimates the spectrum of usage of text annotations to cater to the demands of the AI revolution across various industries.

Traditionally, this is used to be a manual job but not anymore. Clearly Generative AI has given us this immense advantage of textual intelligence already and it is… Read the full blog for free on Medium.

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Published via Towards AI