A social media company is developing an AI to moderate user-generated comments. Initially, they hired human reviewers to rate each sentence (segment) of a comment on a scale of 1 (very safe) to 5 (very harmful). They found that reviewers struggled to consistently assign scores, especially between 2, 3, and 4, leading to noisy data for training the AI. The company's moderation policy has three specific, non-negotiable rules: no hate speech, no personal attacks, and no spam. Based on the challenges described, propose a more effective method for labeling the comment segments to create a better training dataset for the moderation AI. Explain why your proposed method would be an improvement over the 1-5 continuous scoring system in this specific context.