Datasets:
metadata
task_categories:
- token-classification
license: cc-by-4.0
configs:
- config_name: default
data_files:
- split: train
path: extractions.jsonl
datause_raw_extractions
Raw World Bank document extractions (one document per line).
Each row has two columns:
doc_id— the document'smetadata.id.doc— a JSON string holding the full record (metadata+model_extractions, where eachmodel_extractionsentry is one page withinput_text,datasets,classifier_skipped,skip_reason).
from datasets import load_dataset
import json
ds = load_dataset('rafmacalaba/datause_raw_extractions')['train']
record = json.loads(ds[0]['doc'])