# ADR 0004: Chunking strategy for drug monographs — validated against real per-section measurements

## Status

Accepted for the monograph range (printed pp. 99-1496) only. General
chapters (pp. 37-98) and appendices (pp. 1497-1528) are explicitly out of
scope — see Consequences.

## Context

`docs/architecture.md`'s original "Chunking" paragraph specified `(drug,
section)` as the chunk unit, a ~500-800 token budget, and a 400-token/
50-overlap sliding window for oversized sections. Those numbers were written
before segmentation existed — a plausible guess, never checked against real
per-section text length.

Phase 1 (extract → segment → validate) is now real, tested code producing
682 real monographs from the full 1668-page source PDF. This session ran
`python -m ingestion.cli run` for real and measured actual per-section
length across the whole corpus with a temporary investigation script
(`ingestion/scratch/chunking_stats_survey.py`, deleted after this ADR
captured its findings, per this project's investigation-script rule) —
something that had never been measured before this ADR.

## What was actually measured (whole corpus, 682 monographs)

- Sections per monograph: min 11, median 17, max 19 (of ~18-19 known
  section keys in `segment/vocab.py`'s open taxonomy).
- Whole-monograph length: median 11,480 chars, p90 19,068 chars, max 38,786
  chars.
- Per-section length, converted to a **chars/4 token estimate — an
  estimate, not a real tokenizer count**:
  - Most of the ~18 section types sit comfortably under 800 estimated
    tokens even at their p90 (e.g. `chi_dinh` p90≈268 tok, `dang_thuoc_va_
    ham_luong` p90≈115 tok, `tac_dung_khong_mong_muon` p90≈481 tok).
  - **Two sections routinely exceed 800 tokens**:
    `duoc_ly_va_co_che_tac_dung` (242 of 678 monographs that have this
    section, 35.7%, max ≈3542 tok) and `lieu_luong_va_cach_dung` (200 of
    675, 29.6%, max ≈3631 tok).
  - A smaller tail also exceeds it: `than_trong` (25/680, 3.7%),
    `tuong_tac_thuoc` (22/642, 3.4%).
  - This means: the original 800-token ceiling is directionally correct
    (it clears ~16 of 18 section types at their p90 with room to spare),
    but "sub-chunk in that case" is not a rare hedge as originally implied
    — it is the routine path for roughly a third of all monographs, on two
    specific, named, high-clinical-importance sections (mechanism of
    action and dosing).

**A separate, blocking bug was found while gathering this data, not fixed
by this ADR** (out of scope — belongs to `extract`/`segment`, owned by a
parallel session at the time of writing): running header/footer
boilerplate ("DTQGVN 2" + page number + repeated drug name, tagged
`column="full_width"` in `extract/spans.py`) is never filtered out of
section body text before it reaches `SectionSpan.text`. Measured:
1,374 of 11,409 sections (12.0%) contain a literal "DTQGVN" string
mid-text; 671 of 682 monographs (98.4%) have at least one affected section
(e.g. MORPHIN SULFAT's `lieu_luong_va_cach_dung`: `"...Nếu\nDTQGVN 2\n1009\n
Morphin sulfat\nuống viên thuốc..."`). This is `docs/pdf-parsing-outlier-
catalog.md` item 13's known risk, measured whole-corpus for the first time
here. **Chunking must not run against real data until this is fixed** —
otherwise boilerplate is baked into embeddings and can surface mid-sentence
in a chunk shown to a doctor or pharmacist.

## Decision

1. **Chunk unit stays `(drug_id, section_key)`** — matches
   `segment/models.py`'s existing `Monograph.sections: Dict[str,
   SectionSpan]`, matches how a doctor/pharmacist would query ("what does
   it say about liều dùng"), and lets a citation point at one clinical
   section rather than a whole 2,000-19,000-char monograph.
2. **Token budget: keep the 800-token ceiling** (chars/4 estimate) as the
   split trigger. Below it, a section is one chunk, verbatim. This is now a
   validated choice, not a guess.
3. **Sub-chunking only applies to the long-tail sections above** (~30-36%
   of monographs for the two named sections, a few percent for the rest).
   Method: **sentence-boundary-aware sliding window**, replacing the
   originally-guessed fixed-character window. Target ~600-700 tokens per
   sub-chunk (headroom under the 800 ceiling), ~1 sentence / 50-80 token
   overlap between adjacent sub-chunks. Split only at a sentence boundary
   (`.`/`;`/`:` followed by whitespace + capital letter), explicitly not
   treating a Vietnamese decimal comma (e.g. "0,425") as a boundary.
4. **Why sentence-aware, not line- or character-based**: `assembler.py`
   joins `body_lines` one line per PyMuPDF *span*, i.e. one PDF visual
   line-wrap point — not a semantic paragraph or sentence boundary. A blind
   character/line window can split a sentence mid-way. This is a real,
   measured risk here, not theoretical: outlier-catalog item 17 found
   adult/child dosing splits ("Người lớn"/"Trẻ em") appear on 1,121 of
   ~1,400 monograph-range pages — a chunk boundary landing inside one of
   those sentences would be a patient-safety-relevant defect, not a
   cosmetic one.
5. **Chunk metadata / provenance** (extends the existing `drug_name,
   section_type, source_page_range, chunk_id` list in `docs/architecture.md`
   — per this project's provenance convention): `chunk_id`
   (`{drug_id}__{section_key}__{part_index}`), `drug_id`, `drug_name`,
   `section_key`, `section_display_name`, `atc_codes` (inherited from the
   monograph — enables ATC-class-filtered retrieval), exact per-chunk
   `source_page_range` and `printed_page_range`, `part_index`/`part_count`
   (`0`/`1` for un-split sections, keeps the schema uniform across all chunks).
6. **Schema v4 separates source from retrieval context.** `source_text` is the
   exact contiguous source span and is the basis for lossless reassembly and
   page provenance. `text` may prefix repeated route/population labels so a
   continuation chunk is independently safe to retrieve. Those retrieval-only
   prefixes are recorded in `context_labels` and may not alter `source_text`.
   Token counts use `cl100k_base`, not the earlier chars/4 estimate.

## Consequences

- **Scope**: this decision covers the monograph range only. General
  chapters and appendices contain real tables and 2D stacked-fraction
  formulas (`docs/document-profile.md`, investigation in progress as of
  this ADR) that need their own structural survey before any chunking rule
  can be designed for them — do not extend this ADR's rules to those ranges
  without a fresh investigation.
- **Hard prerequisite**: the boilerplate-leakage bug described above must
  be fixed in `extract`/`segment` before this chunking design is run
  against real data for ingestion. This ADR does not fix it.
- **Known gap — sub-compound tagging inside class-level monographs**: 25.5%
  of the corpus has more than one ATC code per monograph (outlier item
  12a), e.g. "VITAMIN D VÀ CÁC THUỐC TƯƠNG TỰ" documents dosing for 7
  different analogues inside one `lieu_luong_va_cach_dung` section. No
  reliable structural signal was found in sampled text to split a section
  by sub-compound — a chunk from this section is tagged with the class
  name only, not the specific analogue a query might target. Deferred to
  golden-dataset-driven eval rather than guessed at now.
- **Resolved — sub-chunk page precision**: schema v4 derives exact physical
  support from the contiguous `source_text` span and maps it to verified
  printed folios. Missing or ambiguous support fails readiness rather than
  falling back to monograph-level provenance.
- **Implemented**: the sentence/label-aware splitter is in
  `ingestion/ingestion/chunk/` with regression tests for dose continuations,
  compound label boundaries, parent route context and lossless reassembly.