Datasets:

rafmacalaba
/

data-use-mention-sft

license: cc-by-4.0
tags:
  - instruction-following
  - sft
  - data-mentions
  - extraction
configs:
  - config_name: default
    data_files:
      - split: train
        path: train.jsonl
      - split: val
        path: val.jsonl
      - split: holdout
        path: holdout.jsonl

Data-mention extraction SFT

Single-task ChatML messages dataset for data-mention extraction, built from the GLiNER2 labels in rafmacalaba/data-use-mentions. Static instructions live in the system message; dynamic text in the user message; the assistant emits compact JSON {"data_mentions":[{"data_mention":"<span>","specificity_type":"named|descriptive|vague"}]} (or {"data_mentions":[]} when none qualify).

Each row also carries corpus (prwp or fcv) and origin (e.g. general_prwp, fcv_pads_east_asia, jdc_operational, refugee_pads, reliefweb) for corpus/origin-filtered training. Filter with finetune_lfm2_data_mention.py --corpus prwp (or --origin ...).

{"train": 59970, "val": 12325, "holdout": 12531}