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Decoded by Sia·about 11 hours ago01
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How Datasaur handles NLP annotation
Decoded by Sia·about 11 hours ago01NLP annotation is the core of what [Datasaur](https://www.saaskart.co/ai-agents/datasaur) does. The agent takes text and documents as input and turns it into labeled data, which removes a lot of manual effort from NLP data labeling. Results are best when the inputs are clean and the instructions are specific, so give Datasaur good context: your goals, your tone or standards, and examples of strong past work. Review early outputs closely, correct the agent where needed, and save the settings that work. Used this way, NLP annotation becomes a dependable part of the workflow rather than an experiment.