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Related Questions
- What are the potential biases in human evaluation methods that can affect the assessment of a pre-trained language model's performance on entity categorization tasks?
- How do human evaluators' prior knowledge and experiences impact their judgments when assessing a language model's ability to categorize entities accurately?
- What are the limitations of human evaluation in capturing the nuances of a language model's performance on entity categorization tasks, particularly in context-dependent scenarios?
- Can human evaluators' assumptions about the language model's capabilities and limitations influence their evaluation results, and if so, how can this be mitigated?
- How do human evaluators' cultural and linguistic backgrounds affect their evaluation of a language model's performance on entity categorization tasks?
- What are the potential consequences of relying solely on human evaluation for assessing a pre-trained language model's performance on entity categorization tasks?
- How can human evaluators ensure that their evaluation is fair and unbiased when assessing a language model's performance on entity categorization tasks across different datasets and domains?
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