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Related Questions
- What are some common challenges that human annotators face when labeling data for machine learning models?
- How can human annotators ensure that their labeling decisions are objective and unbiased?
- What are some strategies for maintaining consistency in labeling data across different annotators?
- What role does active learning play in ensuring consistency in data labeling?
- How can human annotators handle ambiguous or unclear data points during the labeling process?
- What are some best practices for providing clear and concise labeling guidelines to human annotators?
- Can you suggest some techniques for evaluating the quality and consistency of labeled data?
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