What are the common challenges in data annotation?

What are the common challenges in data annotation?

Some common challenges include ensuring data quality, managing large datasets, and dealing with ambiguous labels.

How can we improve data quality during annotation?

Improving data quality can involve using clear guidelines, regular training for annotators, and implementing quality checks.

What tools can help with data annotation?

There are several tools like Labelbox, Amazon SageMaker Ground Truth, and Prodigy that can streamline the annotation process.

How do we handle ambiguous labels?

Handling ambiguous labels often requires establishing a consensus among annotators or using a majority voting system.

What role does automation play in data annotation?

Automation can significantly speed up the annotation process, but it requires careful oversight to ensure accuracy.