rafmacalaba/datause-encoder-data
datause-encoder-data Training data for the data-use encoder: a page-level has_data gate plus a document-level teratopic domain classifier, in one joint dataset. Columns (same schema on every row): task — gate (page-level binary) or domain (document-level multi-label) doc_id — source document id text — page text (gate) or title+abstract (domain) has_data — 0/1 for gate rows (0 placeholder on domain rows) labels — teratopic label list for domain rows (empty on gate rows) Splits… See the full description on the dataset page: https://huggingface.co/datasets/rafmacalaba/datause-encoder-data.
datause-encoder-data
Training data for the data-use encoder: a page-level has_data gate plus a document-level teratopic domain classifier, in one joint dataset.
Columns (same schema on every row):
task—gate(page-level binary) ordomain(document-level multi-label)doc_id— source document idtext— page text (gate) or title+abstract (domain)has_data— 0/1 for gate rows (0 placeholder on domain rows)labels—teratopiclabel list for domain rows (empty on gate rows)
Splits are document-id disjoint across both tasks. The 30 teratopic labels (in column order) are in encoder_labels.json.
