What is data annotation for NLP?
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What is data annotation for NLP?
Data annotation for NLP involves labeling text data to help machine learning models understand and process human language.
Why is data annotation important in NLP?
It's crucial because annotated data improves the accuracy of NLP models by providing them with context and meaning.
What are some common techniques used in data annotation?
Common techniques include entity recognition, sentiment analysis, and part-of-speech tagging.
How can I get started with data annotation?
You can start by using annotation tools like Prodigy or Labelbox, and practicing on publicly available datasets.
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