README.md

metadata

configs:
  - config_name: default
    data_files:
      - split: train
        path:
          - rulings/*.jsonl
task_categories:
  - text-classification
tags:
  - annotation
  - data-mentions
  - human-feedback
license: apache-2.0

Data-use annotations

Public store of keep/drop rulings from the annotation review app (human_labeling/review.html).

Files

• rulings/<annotator>.jsonl — one file per annotator, one JSON object per ruling: key (span UID), ruling (DATA_MENTION keep / NON_MENTION drop), queue (gold / sample), annotator (required, set in the UI), ts. Last write per (queue, key, annotator) wins.

from datasets import load_dataset
ds = load_dataset("rafmacalaba/data-use-annotations")  # train = rulings.jsonl

Note: rulings/_schema.jsonl is a schema placeholder so the dataset always loads — filter annotator != "_schema" in analysis.