Fixed-prompt baseline inputs
Each mini_dev_{sqlite,mysql,postgresql}.jsonl contains 500 inputs aligned to
the current ../data/ files, question IDs 0–499. Send only the
row's prompt to a model. The separate SQL field is evaluation metadata,
not a model input. These files are prompts, not newly collected predictions
or benchmark scores.
The established fixed prompt wording and field order are unchanged. The schema text for each database is reused byte-for-byte from the previous published baseline and checked against all 33 published schema hashes. Only the annotation fields and the question/evidence block have been refreshed from the finalized Mini-Dev 1024 records. No old question or gold SQL was used to fill the new annotations.
prompt_template.txt: exact machine-rendered template.schemas/: the three pinned database-to-schema maps.validate_baseline_inference.py: standalone checks for annotations, prompt rendering and pinned template/input/schema hashes.
Check offline from a downloaded repository snapshot, using Python 3.11 or newer. No hosted databases, model endpoints, keys or Dev release checkout are required:
python baseline_inference/validate_baseline_inference.py
The validator needs only the files in this directory and the sibling data/
directory. The default Hugging Face configuration loads only
data/, not these expanded prompts. Join predictions by dialect and
question_id; use the original strict EX metric, not the cross-dialect
reference-comparison tolerance.