Toxicity Annotation
Labeling harmful or abusive language patterns in text.
Toxicity annotation labels text along a harm axis — typically a severity scale from benign to clearly abusive — covering harassment, insults, threats, and degrading language. It's narrower than full content moderation labeling, which spans many policy categories, and narrower than hate speech labeling specifically, which requires a protected-group target rather than general abuse.
The hardest part of this task is context: the same phrase can be toxic, reclaimed, quoted, or satirical depending on who's saying it and why, which is why toxicity guidelines usually require annotators to consider surrounding context rather than judging a sentence in isolation.
Toxicity datasets train both standalone content filters and the safety behavior evaluated during response safety grading of model outputs.
What this means for trainers
Judge the sentence in its full context, not in isolation — the same words quoted, discussed, or used in fiction carry a different toxicity judgment than the same words used as a direct attack.
Related terms
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