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Related Questions
- What are some common pitfalls that annotators should avoid when labeling negative examples in text classification tasks?
- How can annotators ensure consistency when labeling negative examples across different contexts and domains?
- What are some examples of ambiguous or nuanced cases that annotators may encounter when labeling negative examples?
- How can annotators handle uncertainty or ambiguity when labeling negative examples in a dataset?
- What are some strategies for mitigating annotation bias when labeling negative examples across different contexts?
- How can annotators ensure that their labeling of negative examples is consistent with the task requirements and evaluation metrics?
- What are some common errors that annotators may make when labeling negative examples, and how can they be avoided?
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