ToxSyn-PT: A Large-Scale Synthetic Dataset for Hate Speech Detection in Portuguese

We present ToxSyn-PT, the first large-scale Portuguese corpus that enables fine-grained hate-speech classification across nine legally protected minority groups. The dataset contains 53,274 synthetic sentences equally distributed between minorities groups and toxicity labels. ToxSyn-PT is created through a novel four-stage pipeline: (1) a compact, manually curated seed; (2) few-shot expansion with an instruction-tuned LLM; (3) paraphrase-based augmentation; and (4) enrichment, plus additional neutral texts to curb overfitting to group-specific cues. The resulting corpus is class-balanced, stylistically diverse, and free from the social-media domain that dominate existing Portuguese datasets. Despite domain differences with traditional benchmarks, experiments on both binary and multi-label classification on the corpus yields strong results across five public Portuguese hate-speech datasets, demonstrating robust generalization even across domain boundaries. The dataset is publicly released to advance research on synthetic data and hate-speech detection in low-resource settings.