File size: 5,218 Bytes
27c633b | 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 73 74 75 76 77 78 79 | #!/usr/bin/env python3
"""Append a frozen, sourced and reviewed 500-question supplement to unchanged v6.2."""
import hashlib
import json
import unicodedata
from collections import Counter
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
BASE_SHA = 'aaceb71c48331b813049f35bdb103d630f4acd46caeea2db831108f962f17630'
AUTHOR = 'Claude Opus 5.5 (Anthropic), via parallel authoring agents'
DATE = '2026-10-14'
SELECTION = ('Authored and reviewed before any model was evaluated on these additions; '
'no performance-based item selection')
def sha(data):
return hashlib.sha256(data).hexdigest()
def build():
base = ROOT / 'data/v6.2/test.jsonl'
assert sha(base.read_bytes()) == BASE_SHA
rows = [json.loads(s) for s in base.read_text().splitlines()]
source = [json.loads(s) for s in (ROOT / 'source/v6.3-additions.jsonl').read_text().splitlines()]
assert len(source) == 500
audit = []
for line, item in enumerate(source, 1):
question = unicodedata.normalize('NFC', item['question']).strip()
qid = 'aussieqa-' + sha(question.encode())[:20]
rows.append({'id': qid, 'question': question, 'answers': [item['answer']]})
audit.append({'id': qid, 'source_version': '6.3-additions', 'source_line': line,
'topic': item['topic'], 'subtopic': item['subtopic'],
'difficulty_estimate': item['difficulty_estimate'], 'source_url': item['source_url'],
'author': AUTHOR, 'authored_date': DATE, 'answer_source_checked_date': DATE,
'review': item['review'], 'selection': SELECTION})
assert len(rows) == len({r['id'] for r in rows}) == len({r['question'].casefold() for r in rows}) == 1500
for path, data in [('data/v6.3/test.jsonl', rows), ('metadata/v6.3/additions.jsonl', audit)]:
p = ROOT / path
p.parent.mkdir(parents=True, exist_ok=True)
p.write_text(''.join(json.dumps(r, ensure_ascii=False, separators=(',', ':')) + '\n' for r in data))
assert (ROOT / 'data/v6.3/test.jsonl').read_bytes().startswith(base.read_bytes())
outcomes = Counter(item['review']['outcome'] for item in source)
manifest = {'dataset': 'Aussie-1k', 'version': '0.4', 'source_build_identifier': '6.3', 'release_date': DATE,
'base_version': '0.3', 'unchanged_base_questions': 1000, 'new_questions': 500,
'test_records': 1500, 'reference_answers': sum(len(r['answers']) for r in rows),
'answer_count_distribution': dict(Counter(len(r['answers']) for r in rows)),
'addition_topic_counts': dict(Counter(r['topic'] for r in source)),
'addition_subtopic_slices': dict(Counter(r['slice'] for r in source)),
'addition_difficulty_estimates': dict(sorted(Counter(r['difficulty_estimate'] for r in source).items())),
'review_outcomes': dict(outcomes),
'review_protocol': ('Claude authored each item and checked it against the cited source. MiniMax-M3 and '
'GLM-5.3-Flash (SCX.ai) independently rated fit (1-5), reference correctness, ambiguity '
'and time-stability. Items accepted by both judges with no flags passed review; every '
'flagged item was adjudicated by Claude against sources and kept unchanged, revised and '
're-reviewed by both judges, or dropped. Claude then read every remaining candidate and '
'dropped overlapping, answer-leaking or weakly attested items.'),
'selection_rule': ('From the reviewed candidates, 45 items per authoring slice (50 for geography); within '
'each slice, difficulty levels keep proportional shares and items are ranked by the '
'judges\' summed fit scores. No evaluated-model answers were used.'),
'candidate_counts': {'drafted': 608, 'dropped_as_duplicates_or_unstable_before_review': 14,
'dropped_in_adjudication_or_manual_review': 12, 'reserve_not_selected': 82,
'selected': 500},
'duplicate_review': ('Exact and case-insensitive uniqueness checked; semantic near-duplicates against '
'v6.2 and within the supplement flagged with E5-Mistral-7B-Instruct embeddings '
'(cosine >= 0.82) and resolved by hand. No claim of exhaustive semantic deduplication.'),
'ordering': 'Unchanged v6.2 questions followed by 500 additions in frozen source order',
'files': {}}
for name in ['data/v6.2/test.jsonl', 'source/v6.3-additions.jsonl', 'data/v6.3/test.jsonl',
'metadata/v6.3/additions.jsonl']:
b = (ROOT / name).read_bytes()
manifest['files'][name] = {'sha256': sha(b), 'bytes': len(b)}
(ROOT / 'metadata/v6.3/manifest.json').write_text(json.dumps(manifest, indent=2) + '\n')
print(json.dumps(manifest, indent=2))
if __name__ == '__main__':
build()
|