Datasetpublic

rafmacalaba/data-use-annotations

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") #… See the full description on the dataset page: https://huggingface.co/datasets/rafmacalaba/data-use-annotations.

sourceHugging Faceapache-2.0updated 12d agoView on Hugging Face

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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.

python

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.