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Related Questions
- What are the key factors that influence the trade-off between annotation quality and quantity in NER evaluation?
- How do different annotation schemes, such as crowdsourcing and expert annotation, address the trade-off between quality and quantity?
- What are the potential consequences of prioritizing one aspect of the trade-off over the other in NER evaluation?
- Can you explain the concept of 'annotation density' and how it relates to the trade-off between quality and quantity?
- How do active learning strategies, such as uncertainty sampling and query-by-committee, impact the trade-off between annotation quality and quantity?
- What are the limitations of using automated annotation tools, such as rule-based systems and machine learning models, to address the trade-off?
- Can you discuss the role of human evaluators in ensuring annotation quality and quantity in NER evaluation, and how their involvement can impact the trade-off?
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