Order 20260904T172353Z-6290714297-from-.claude. Bilag 9.1's 95.1 % CID share (docs/2026-09-04-k3-arm-c.md) was found ad hoc, with no committed script -- the same gap this repo's own fidelity instrument criticizes in Arm A's uncommitted docx/xlsx figures. okf_cid_measure.py runs the exact extract_text call the door makes and reports per-document CID share and 4+-letter word count, denominator stated for files it cannot measure. Red-first: tests/test_cid_measure.py pins measure() against fixture text of known composition before the implementation existed. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
129 lines
4.9 KiB
Python
129 lines
4.9 KiB
Python
"""Measure the CID-glyph share of every document in a corpus. Measure, don't build.
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Order 20260904T172353Z-6290714297-from-.claude. `docs/2026-09-04-k3-arm-c.md`
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found that Bilag 9.1 -- the largest concept in the K2 bundle -- is an
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extraction failure, not a segmentation failure: 95.1 % of its extracted text
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is `(cid:N)` glyph codes, the shape `pdfminer.six` (behind `pdfplumber`, this
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library's PDF reader) emits when a font carries no usable ToUnicode mapping.
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This instrument answers whether Bilag 9.1 is alone in the corpus, or whether
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the CID failure reaches other documents -- a K1-arm (door-level) question, not
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a K3 one. It builds nothing: no CID-mapped extraction path, no new extractor.
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Runs the SAME extraction call the door makes (`extract_text`), never a second
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parser -- a number from a different code path would answer a different
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question than "what does this repository actually persist."
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`(cid:N)` and "four or more letters" are THIS instrument's own definitions,
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not upstream terms; both are named here rather than assumed.
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"""
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from __future__ import annotations
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import argparse
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import re
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import sys
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from dataclasses import dataclass
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "src"))
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from llm_ingestion_okf.errors import ExtractionError # noqa: E402
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from llm_ingestion_okf.extract import extract_text # noqa: E402
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#: What "a CID glyph code" means here -- pdfminer.six's placeholder for a
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#: character its font's encoding cannot map to Unicode. Not an upstream term:
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#: this is the shape observed in the extracted text, not a spec.
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_CID = re.compile(r"\(cid:\d+\)")
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#: "An alphabetic word of four or more letters" -- the same measure used on
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#: Bilag 9.1 in `docs/2026-09-04-k3-arm-c.md`. Unicode letters (so æøå count),
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#: digits and `_` excluded, so a `(cid:12)` code's "cid" (3 letters) never
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#: qualifies and the CID codes cannot inflate this count.
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_WORD = re.compile(r"[^\W\d_]{4,}", re.UNICODE)
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@dataclass(frozen=True)
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class CidMeasurement:
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total_chars: int
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cid_chars: int
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word_count: int
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@property
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def pct(self) -> float:
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return 100.0 * self.cid_chars / self.total_chars if self.total_chars else 0.0
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def measure(text: str) -> CidMeasurement:
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cid_chars = sum(len(match.group(0)) for match in _CID.finditer(text))
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word_count = len(_WORD.findall(text))
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return CidMeasurement(total_chars=len(text), cid_chars=cid_chars, word_count=word_count)
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@dataclass(frozen=True)
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class Row:
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"""One corpus file's result: either measured, or a stated reason it was not."""
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name: str
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measurement: CidMeasurement | None
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skip_reason: str | None
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def line(self) -> str:
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if self.measurement is None:
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return f"| {self.name} | -- | -- | -- | -- | not measured: {self.skip_reason} |"
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m = self.measurement
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return (
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f"| {self.name} | {m.total_chars} | {m.cid_chars} | {m.pct:.1f} % | {m.word_count} | |"
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)
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def run(corpus: Path) -> list[Row]:
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rows: list[Row] = []
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for path in sorted(corpus.iterdir(), key=lambda p: p.name):
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if not path.is_file():
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continue
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try:
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text = extract_text(path.name, path.read_bytes())
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except ExtractionError as exc:
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rows.append(Row(name=path.name, measurement=None, skip_reason=f"{exc.code}: {exc}"))
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continue
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rows.append(Row(name=path.name, measurement=measure(text), skip_reason=None))
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return rows
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def render(corpus: Path, rows: list[Row]) -> str:
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measured = [row for row in rows if row.measurement is not None]
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over_10 = sum(
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1 for row in measured if row.measurement is not None and row.measurement.pct > 10.0
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)
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over_50 = sum(
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1 for row in measured if row.measurement is not None and row.measurement.pct > 50.0
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)
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lines = [
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f"# CID-glyph share, {corpus}",
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"",
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f"N = {len(rows)} (corpus directory file count). Measured: {len(measured)}/{len(rows)}.",
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f"Over 10 %: {over_10}/{len(measured)}. Over 50 %: {over_50}/{len(measured)}.",
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"",
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"| file | total chars | cid chars | cid share | words (4+ letters) | |",
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"|---|---|---|---|---|---|",
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]
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lines.extend(row.line() for row in rows)
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return "\n".join(lines) + "\n"
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def main(argv: list[str] | None = None) -> int:
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--corpus", type=Path, required=True, help="the directory to measure")
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parser.add_argument("--report", type=Path, required=True, help="where to write the table")
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args = parser.parse_args(argv)
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if not args.corpus.is_dir():
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print(f"okf-cid-measure: FAILED - no corpus directory at {args.corpus}", file=sys.stderr)
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return 1
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rows = run(args.corpus)
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args.report.write_text(render(args.corpus, rows), encoding="utf-8")
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print(f"okf-cid-measure: wrote {args.report}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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