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f67cae0 | 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 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 | #!/usr/bin/env python3
"""Build per-question E2E v3 structure shards for a static viewer."""
from __future__ import annotations
import argparse
import base64
import gzip
import json
import shutil
from collections import defaultdict
from pathlib import Path
from typing import Any, Iterator
ROOT = Path(__file__).resolve().parent.parent
DEFAULT_SHAPES = [
"tabular_records",
"chronology_and_timeline_indexes",
"claim_and_theme_summaries",
"qa_shortcuts_and_templates",
"relation_graphs_and_mappings",
]
def iter_jsonl(path: Path) -> Iterator[dict[str, Any]]:
with path.open(encoding="utf-8") as handle:
for line_number, line in enumerate(handle, 1):
if not line.strip():
continue
value = json.loads(line)
if not isinstance(value, dict):
raise ValueError(f"{path}:{line_number}: expected an object")
yield value
def load_shape_index(
scaffolds_dir: Path, shape: str
) -> tuple[str, dict[str, list[dict[str, str]]]]:
index_path = scaffolds_dir / shape / "_index.json"
if not index_path.exists():
raise FileNotFoundError(f"missing shape index: {index_path}")
payload = json.loads(index_path.read_text(encoding="utf-8"))
files: dict[str, list[dict[str, str]]] = defaultdict(list)
for entry in payload.get("entries", []):
if entry.get("doc_id") is None or not entry.get("file"):
continue
files[str(entry["doc_id"])].append(
{
"file": str(entry["file"]),
"unit_name": str(entry.get("unit_name") or ""),
"unit_description": str(entry.get("unit_description") or ""),
}
)
return str(payload.get("description") or ""), dict(files)
def load_bundle_map(path: Path | None) -> dict[str, str]:
if path is None:
return {}
mapping: dict[str, str] = {}
for row in iter_jsonl(path):
physical_id = str(row["physical_id"])
for source_id in row.get("source_doc_ids", []):
source_id = str(source_id)
if source_id in mapping:
raise ValueError(f"duplicate bundle mapping for {source_id}")
mapping[source_id] = physical_id
return mapping
def structure_format(filename: str) -> str:
suffixes = Path(filename).suffixes
if filename.endswith(".timeline.json"):
return "json"
if filename.endswith(".edges.jsonl"):
return "jsonl"
return suffixes[-1].lstrip(".").lower() if suffixes else "txt"
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--dataset", required=True)
parser.add_argument("--unified", type=Path, required=True)
parser.add_argument("--scaffolds-dir", type=Path, required=True)
parser.add_argument("--bundle-manifest", type=Path)
parser.add_argument("--out", type=Path, default=ROOT / "e2e_structures_v3")
parser.add_argument("--label", default="E2E Structures v3")
parser.add_argument("--shapes", default=",".join(DEFAULT_SHAPES))
return parser.parse_args()
def main() -> None:
args = parse_args()
shapes = [value.strip() for value in args.shapes.split(",") if value.strip()]
if not shapes:
raise ValueError("--shapes must contain at least one shape")
shape_descriptions: dict[str, str] = {}
shape_files: dict[str, dict[str, list[dict[str, str]]]] = {}
for shape in shapes:
description, files = load_shape_index(args.scaffolds_dir, shape)
shape_descriptions[shape] = description
shape_files[shape] = files
print(f"{shape:38s} {len(files):>6} extraction docs")
bundle_map = load_bundle_map(args.bundle_manifest)
records_dir = args.out / "records"
if records_dir.exists():
shutil.rmtree(records_dir)
records_dir.mkdir(parents=True, exist_ok=True)
index_rows: list[dict[str, Any]] = []
extraction_docs_seen: set[str] = set()
source_docs_seen: set[str] = set()
source_docs_unmapped: set[str] = set()
extraction_docs_without_structures: set[str] = set()
total_structures = 0
for row in iter_jsonl(args.unified):
grouped: dict[str, list[dict[str, Any]]] = {}
group_order: list[str] = []
for doc in row.get("docs", []) or []:
source_id = str(doc.get("id"))
source_docs_seen.add(source_id)
extraction_id = bundle_map.get(source_id, source_id)
if bundle_map and source_id not in bundle_map:
source_docs_unmapped.add(source_id)
if extraction_id not in grouped:
grouped[extraction_id] = []
group_order.append(extraction_id)
grouped[extraction_id].append(
{"doc_id": source_id, "contents": str(doc.get("contents") or "")}
)
per_doc: list[dict[str, Any]] = []
question_structures = 0
for extraction_id in group_order:
extraction_docs_seen.add(extraction_id)
structures: list[dict[str, Any]] = []
for shape in shapes:
for entry in shape_files[shape].get(extraction_id, []):
filename = entry["file"]
path = args.scaffolds_dir / shape / filename
structures.append(
{
"shape_id": shape,
"description": shape_descriptions[shape],
"file": filename,
"unit_name": entry["unit_name"],
"unit_description": entry["unit_description"],
"format": structure_format(filename),
"content": path.read_text(encoding="utf-8")
if path.exists()
else "",
}
)
if not structures:
extraction_docs_without_structures.add(extraction_id)
question_structures += len(structures)
source_docs = grouped[extraction_id]
per_doc.append(
{
"doc_id": extraction_id,
"source_doc_ids": [doc["doc_id"] for doc in source_docs],
"source_docs": source_docs,
"is_supporting": True,
"n_structures": len(structures),
"contents": "\n\n".join(
f"===== {doc['doc_id']} =====\n{doc['contents']}"
for doc in source_docs
),
"structures": structures,
}
)
qid = str(row["qid"])
record = {
"qid": qid,
"dataset": args.dataset,
"question": row.get("question"),
"gold_answers": row.get("answers", []),
"n_docs": len(per_doc),
"n_source_docs": sum(len(doc["source_doc_ids"]) for doc in per_doc),
"n_structures": question_structures,
"docs": per_doc,
}
raw = json.dumps(record, ensure_ascii=False, separators=(",", ":")).encode()
encoded = base64.b64encode(gzip.compress(raw, compresslevel=9)).decode("ascii")
relative_path = f"records/{qid}.json.gzip.b64"
(args.out / relative_path).write_text(encoded, encoding="ascii")
index_rows.append(
{
"qid": qid,
"question": row.get("question"),
"n_docs": len(per_doc),
"n_source_docs": record["n_source_docs"],
"n_structures": question_structures,
"doc_ids": [doc["doc_id"] for doc in per_doc],
"source_doc_ids": [
source_id
for doc in per_doc
for source_id in doc["source_doc_ids"]
],
"path": relative_path,
}
)
total_structures += question_structures
meta = {
"label": args.label,
"dataset": args.dataset,
"n_qids": len(index_rows),
"n_extraction_docs": len(extraction_docs_seen),
"n_source_docs": len(source_docs_seen),
"n_source_docs_unmapped": len(source_docs_unmapped),
"n_extraction_docs_without_structures": len(
extraction_docs_without_structures
),
"n_structures_total": total_structures,
"shapes": shapes,
"shape_descriptions": shape_descriptions,
"scaffolds_dir": str(args.scaffolds_dir),
"unified": str(args.unified),
"bundle_manifest": str(args.bundle_manifest) if args.bundle_manifest else None,
}
args.out.mkdir(parents=True, exist_ok=True)
(args.out / "index.json").write_text(
json.dumps({"meta": meta, "rows": index_rows}, ensure_ascii=False),
encoding="utf-8",
)
print(json.dumps(meta, indent=2))
if __name__ == "__main__":
main()
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