README.md

---
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`](https://huggingface.co/datasets/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 `passages` chunk 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 in `gold_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`](https://huggingface.co/datasets/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.