Datasets:

rafmacalaba
/

datause-extracted-human473-docs

configs:
  - config_name: gliner
    data_files:
      - split: train
        path: gliner_train.jsonl
      - split: val
        path: gliner_val.jsonl
      - split: holdout
        path: gliner_holdout.jsonl
  - config_name: bio
    data_files:
      - split: train
        path: bio_train.jsonl
      - split: val
        path: bio_val.jsonl
      - split: holdout
        path: bio_holdout.jsonl
  - config_name: gliner2
    data_files:
      - split: train
        path: gliner2_train.jsonl
      - split: val
        path: gliner2_val.jsonl
      - split: holdout
        path: gliner2_holdout.jsonl
  - config_name: passages
    data_files:
      - split: train
        path: passages_train.jsonl
license: cc-by-4.0
task_categories:
  - token-classification
tags:
  - ner
  - span-extraction
  - data-mentions
  - economics

datause-extracted-human473-docs

Every passage of the 162 documents behind the 473 human-validated holdout spans of the data-use annotation campaign:

population	spans	documents
`annotator190`	190	134
`jdc283`	283	28
total	473	162

Configs

gliner, bio, gliner2 — row-for-row subset of rafmacalaba/datause-extracted (revision 15812843687e2ec81b261b5895f2019b50a8f97e): same columns, same split files, rows verbatim. Rows per config: gliner/train 1963, gliner/val 414, gliner/holdout 342, bio/train 1963, bio/val 414, bio/holdout 342, gliner2/train 1963, gliner2/val 414, gliner2/holdout 342. These cover 158 of the 162 documents; the source repo has no rows for the remaining 4 (fcv_pads_east_africa:019636, fcv_pads_east_africa:019977, fcv_pads_east_africa:013470, fcv_pads_east_africa:013125).
passages — the complete chunk set of all 162 documents (14568 rows), taken from the upstream extraction meta rafmacalaba/fcv-extractions-meta-tiered. Columns: population`, `corpus_id`, `doc_id`, `page`, `chunk`, `origin`, `title`, `pdf_url`, `project_id`, `country`, `document_type`, `input_text. Use this config when the question is "what text do these documents contain" — it is the only view that includes the 4 documents datause-extracted is missing.
gold_spans.jsonl (repo root) — the 473 spans: key, population, surface, human_keep, corpus_id, page, chunk, title, pdf_url, text (the passage the span was annotated in, from rafmacalaba/datause-displacement-reviewed rev 24c1a0e).

Selection

A document is in scope iff it backs at least one of the 473 spans. The span -> document join is corpus_id + page + chunk from the judge sheets (exact, not title-based); datause-extracted rows are kept by pdf_url or corpus_id, so every passage of a selected document is included, spans-free chunks as well.

Surface check: 473/473 gold surfaces occur verbatim inside a passageschunk of their own document. The residual are chunk-boundary and markdown-normalisation artefacts of re-parsing the PDFs, not missing documents; the annotated passage of every span is ingold_spans.jsonl.

Caveats

The source repo's split assignment is not document-disjoint. Documents of this set appear in more than one of train/val/holdout in datause-extracted, so the same document can be in two files here too. The split column is preserved verbatim; these are faithful subsets, not a re-split. Treat train as neither clean nor a contamination-free reference for these documents.
Spans shipped inside gliner/bio/gliner2 are raw model predictions, not gold. Gold labels live in gold_spans.jsonl and in rafmacalaba/datause-displacement-reviewed (probe_reviewed, split holdout, kinds annotator / jdc).
pdf_url is the document key; a handful of title values upstream are generic document-type strings ("Appraisal Project Information Document (PID)").
Provenance of the document set: analysis/holdout_documents_annotator190_jdc283.{json,tsv} in the source project.