add dataset link

README.md

@@ -122,6 +122,32 @@ It performs relative comparison only.
 
 Training performed using Fireworks AI.
 
+## Training Data
+
+This model is fine-tuned via supervised fine-tuning (SFT) with LoRA on pairwise privacy-preference comparisons.
+
+Training labels are generated using a teacher model (OpenAI o3) on [ShareGPT90K](https://huggingface.co/datasets/liyucheng/ShareGPT90K)-derived privacy-variant pairs.  
+As described in the paper, o3 was selected based on its alignment with human ground truth under high-consensus cases.
+
+In addition, we release a human-labeled evaluation set of 150 A/B pairs.  
+Each pair is annotated by at least 5 qualified participants (52 unique participants total), with provided `consensus` labels and `consensus_ratio`.
+
+For details on data construction, model selection, and annotation procedures, please refer to the paper.
+
+---
+## Released Dataset (Human Ground Truth)
+
+We release a human-labeled [dataset](https://github.com/PEACH-Research-Lab/Operationalize-Data-Minimization/blob/main/human_labeled_datasets/DATASET_CARD.md) of 150 pairwise privacy-preference comparisons.
+
+Each JSONL entry contains:
+- `survey_id`, `conversation_id`, `pair_index`
+- `answers`: anonymized participant votes (`participant_1`, `participant_2`, ...)
+- `consensus`, `consensus_ratio`
+- `message_A`, `message_B`
+
+### Participant Privacy
+All participant identifiers are anonymized. No Prolific IDs or direct participant identifiers are released.
+
 ---
 
 ## Model Outputs