File size: 2,485 Bytes
f45e98c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | """Build an eval dataset from DEplain-web-doc (German plain-language doc pairs).
DEplain-web-doc (Stodden et al., ACL 2023) is openly loadable from HuggingFace with no
auth. Each row has an `original` (complex) and a `simplification` (Einfache/Leichte
Sprache) German document, plus CEFR levels and a `corpus` (subcorpus) tag we keep for
register filtering.
We map to the repo's eval-dataset schema ({title, original, human_translated}) and keep
`corpus`/`complex_level`/`simple_level` as extra metadata. This materializes the human original/simplified pairs only.
Run:
python -m data_process.deplain_web
"""
from __future__ import annotations
import json
from pathlib import Path
HF_DATASET = "DEplain/DEplain-web-doc"
SPLITS = ("train", "validation", "test")
def create_deplain_web_json(splits: tuple[str, ...] = SPLITS) -> int:
"""Load DEplain-web-doc (all splits by default) and write the eval dataset.
Returns the number of records written.
"""
from datasets import load_dataset
out_path = Path("data/deplain_web.json")
data: list[dict] = []
for split in splits:
ds = load_dataset(HF_DATASET, split=split)
for i, row in enumerate(ds):
original = (row.get("original") or "").strip()
simplified = (row.get("simplification") or "").strip()
if not original or not simplified:
continue
corpus = row.get("corpus", "")
data.append(
{
"title": f"{corpus}:{split}:{i}",
"original": original,
"human_translated": simplified,
"corpus": corpus,
"complex_level": row.get("complex_level"),
"simple_level": row.get("simple_level"),
"split": split,
}
)
if not data:
print("No DEplain-web records assembled - check dataset access.")
return 0
out_path.parent.mkdir(parents=True, exist_ok=True)
out_path.write_text(
json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8"
)
by_corpus: dict[str, int] = {}
for d in data:
by_corpus[d["corpus"]] = by_corpus.get(d["corpus"], 0) + 1
print(f"Wrote {len(data)} pairs to {out_path}")
print(
"By subcorpus: " + ", ".join(f"{k}={v}" for k, v in sorted(by_corpus.items()))
)
return len(data)
if __name__ == "__main__":
create_deplain_web_json()
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