docs/DATASETS.md

# Datasets

The bundle ships text-free scores, not texts. This page is only for people who hold (or can obtain) a license for the underlying corpora and want to see the text behind a given score. Rebuilding a corpus lets you audit provenance; it does **not** let you recompute the scores, because the scorer is closed.

We redistribute no source text, no simplified text, and no competitor model outputs, only numeric features derived from them. The commands below are access instructions, not a grant of rights: obtain each corpus under its own license.

## The corpora

| Corpus (`dataset` key)                                                     | Access                    | What it is                                                                                                                                                                                                                              |
| -------------------------------------------------------------------------- | ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [**deplain_web**](https://huggingface.co/datasets/DEplain/DEplain-web-doc) | open, scriptable          | DEplain-web-doc (Stodden et al., ACL 2023): German plain-language document pairs, loadable from HuggingFace with no auth.                                                                                                               |
| [**toborek**](https://github.com/mlai-bonn/Simple-German-Corpus)           | public clone              | Toborek et al., "A New Aligned Simple German Corpus": from the public `mlai-bonn/Simple-German-Corpus` repo.                                                                                                                            |
| **apa_lha**                                                                | restricted (author-gated) | APA-LHA (Spring/Stodden): the CEFR-graded (A2/B1) sentence-aligned release of the APA news corpus. Obtain the `APA_sentence-aligned_LHA` release from the authors. Used doc-level (min-words 100) and for the graded-monotonicity test. |
| [**deplain_apa**](https://zenodo.org/records/7674560)                      | restricted (on request)   | DEplain-APA (Stodden et al., ACL 2023): the license-restricted APA half of DEplain, on request via Zenodo `7674560`.                                                                                                                    |

Builder scripts are in [`data_process/`](../data_process/) and are scorer-free: they only map raw sources into the eval schema, with no scorer import.

## How a bundle row maps to a text (`item_id`)

Each bundle row's `item_id` is `"<dataset>:<pair_idx>:<side>"`:

- `pair_idx`: the 0-based index of the record in that dataset's built `eval_dataset.json` (unfiltered, in file order).
- `side`: `orig` = the record's `original`, `simp` = its `human_translated`.

So once you rebuild a corpus, `item_id` `deplain_apa:12:simp` is the `human_translated` field of the 13th record of `data/deplain_apa.json`. Row metadata (`sub`, `meta.level`, `meta.article_id`, `meta.split`) travels in the bundle, so filtering and grouping are reproducible from the bundle alone.

## Rebuilding each corpus

### deplain_web (open, fully scriptable)

```bash
python -m data_process.deplain_web
# -> data/deplain_web.json  (HF: DEplain/DEplain-web-doc)
```

This is the only builder that needs a dependency beyond the analysis stack: `pip install datasets`.

### toborek (clone the public corpus, then build)

```bash
git clone https://github.com/mlai-bonn/Simple-German-Corpus /tmp/Simple-German-Corpus
python -m data_process.toborek --hand-aligned /tmp/Simple-German-Corpus
# use --full <clone> instead, after running that repo's crawler, for the complete set
```

### apa_lha (obtain the APA-LHA release, then build)

Obtain the `APA_sentence-aligned_LHA` release (Spring/Stodden; APA news, author-gated). It extracts to a folder containing `A2-OR/` and `B1-OR/`.

```bash
python -m data_process.apa_lha --root /path/to/APA_sentence-aligned_LHA
```

### deplain_apa (request via Zenodo, then build)

Request access to [Zenodo 7674560](https://zenodo.org/records/7674560) (DEplain-APA) and extract the `DEPlain` download (contains `B__Document-level_Corpus/`, `E__Sentence-level_Corpus/`).

```bash
python -m data_process.deplain_apa --root /path/to/DEPlain
```

## Not included here

- **Competitor model outputs** (erlesen, German4all, ELGEPA, capito): not redistributed (erlesen ships with no declared license). The paper documents each model's checkpoint and decoding contract so they can be regenerated from the public model weights.
- **`deplain_apa_sent`** (13k sentence pairs) and **`simpevalde`**: used only by reference-based metrics (EASSE-DE SARI/BLEU/BERTScore), which are standard and open; they are not part of the closed-scorer bundle.