Datasets:
key string | ruling string | queue string | annotator string | ts timestamp[s] |
|---|---|---|---|---|
_schema | DATA_MENTION | _schema | _schema | 2026-09-09T00:00:00 |
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_MENTIONkeep /NON_MENTIONdrop),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.
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