Add the UK Electoral Commission's individual donors as a local corpus

AGENTS.md

@@ -275,7 +275,7 @@ Add a dedicated `copy.deepcopy()` round-trip test for it too (see `test_regexes_
 
 **Adding a flag-gated post-parse transform** (reorder/adjust) — add a `Constants` boolean (default `False`), implement a `handle_*()` method, and call it in `post_process()` after `handle_firstnames()` and before `handle_capitalization()`, gated on the flag. Default-off keeps existing parses byte-for-byte unchanged. Two shipped examples: `patronymic_name_order` gates both `handle_east_slavic_patronymic_name_order()` (#85) and `handle_turkic_patronymic_name_order()` (#185) — one flag driving two independent handlers, added in the same `post_process()` slot; `middle_name_as_last` gates `handle_middle_name_as_last()` (#133), which folds `middle_list` into `last_list`.
 
-**Validating a new parsing rule** — before implementing, simulate it in a throwaway script against `TEST_NAMES` (plus a few target-language examples) to catch regressions/false-positives early. E.g. this surfaced the `last_base` `do`/`st`/`mc` empties and the patronymic `"David Michael Abramovich"` false-reorder. After the change, `tests/v2/test_snapshot.py` lists every corpus name it moved, grouped by changed field -- read them, and re-record with `uv run python tools/differential/snapshot.py --record` once every move is intended, so the PR diff of `snapshot.jsonl` shows the reviewer the same list. `uv run python tools/differential/cldr_agreement.py` reports how the tree's agreement with CLDR's stated name fields moved; `tests/v2/test_cldr_agreement.py` fails on any move, and `tools/differential/cldr_agreement.json` doubles as a measured list of names the parser and CLDR read differently. The same command and test score the GND corpus's real names (`gnd_fields.jsonl`, record `gnd_agreement.json`) by the same rules, and `--record` rewrites every record, printing per source what it accepts. A locale-pack change reads the second view the same command prints, per pack (`cldr_agreement_locales.json`, #672, and `wikidata_native_agreement_locales.json` for real Han and kana names); its `JA` rows run only with the `ja` extra installed. A change to Han, Hangul or kana order or to Korean segmentation reads `wikidata_native_agreement.json` too: the only real names in those scripts the corpora hold. It holds no honorific, so a change to the honorific peel moves nothing there. A change to comma or credential handling also reads the local corpus of hand-typed names (`snapshot.py --local ctgov-officials`, recorded first against the base checkout with `--tree`; tools/differential/README.md's "Local corpora"): the one population of names nobody chose for a test or a catalog, so it shows how often each shape is typed, and the one no CI run sees.
+**Validating a new parsing rule** — before implementing, simulate it in a throwaway script against `TEST_NAMES` (plus a few target-language examples) to catch regressions/false-positives early. E.g. this surfaced the `last_base` `do`/`st`/`mc` empties and the patronymic `"David Michael Abramovich"` false-reorder. After the change, `tests/v2/test_snapshot.py` lists every corpus name it moved, grouped by changed field -- read them, and re-record with `uv run python tools/differential/snapshot.py --record` once every move is intended, so the PR diff of `snapshot.jsonl` shows the reviewer the same list. `uv run python tools/differential/cldr_agreement.py` reports how the tree's agreement with CLDR's stated name fields moved; `tests/v2/test_cldr_agreement.py` fails on any move, and `tools/differential/cldr_agreement.json` doubles as a measured list of names the parser and CLDR read differently. The same command and test score the GND corpus's real names (`gnd_fields.jsonl`, record `gnd_agreement.json`) by the same rules, and `--record` rewrites every record, printing per source what it accepts. A locale-pack change reads the second view the same command prints, per pack (`cldr_agreement_locales.json`, #672, and `wikidata_native_agreement_locales.json` for real Han and kana names); its `JA` rows run only with the `ja` extra installed. A change to Han, Hangul or kana order or to Korean segmentation reads `wikidata_native_agreement.json` too: the only real names in those scripts the corpora hold. It holds no honorific, so a change to the honorific peel moves nothing there. A change to comma or credential handling also reads the local corpus of hand-typed names (`snapshot.py --local ctgov-officials`, recorded first against the base checkout with `--tree`; tools/differential/README.md's "Local corpora"): the one population of names nobody chose for a test or a catalog, so it shows how often each shape is typed, and the one no CI run sees. A change to title handling reads `ukec-individuals` the same way: UK donors' names in spoken order and mixed case, in 8,219 of whose 15,214 `parse()` read a title on 2026-10-22.
 
 ## Gotchas
 
@@ -313,6 +313,8 @@ Add a dedicated `copy.deepcopy()` round-trip test for it too (see `test_regexes_
 
 **A JSONL file written with `json.dumps(..., ensure_ascii=False)` is cut by `str.splitlines()`** — `json.dumps` leaves U+2028, U+2029 and U+0085 unescaped, and `splitlines()` splits at all three, so one name pasted from a document holding a line separator turns its line into two halves of invalid JSON, and the file into one no reader can load. #801's review found it in the local corpora (a single official among 536,981 would have made the cache unloadable for good), and the review of that fix found it again one file over, in `snapshot.py`'s `dump`/`load`, which the fix had not touched. So it is fixed at the shared source now: `corpus_build.jsonl_line` escapes the three and `corpus_build.jsonl_lines` cuts at `"\n"` only, and `corpus_build`'s corpus and fields writers, `snapshot.py`, `cldr_agreement.py` and `local_corpora.py` go through them. A new JSONL writer or reader in tools/ goes through the same two. Still outside them: the builders that write their own lines (`build_cjk_corpus.py`, `_conventions`, `_shapes`, `_rules`, `_issues`), `compare.py`'s worker stream, and the tests' corpus reads (`_differential_fixtures.py`, `test_corpora.py`); none of the 16 committed JSONL files held one on 2026-10-21.
 
+**A row count does not prove a CSV whole: Python's `csv` returns a body cut inside a row as a short last row, without raising** -- even inside an open quote (`'a,b\r\n"x,y'` gives `[['a', 'b'], ['x,y']]`). So a fetch that checks its row count against the source's stated total, and tolerates a few malformed rows, passes a cut body one name short. #842's review found it in `ukec-individuals` (two reviewers independently); the fix requires the body to end with a line break and its last row not to be short (a cut only shortens a row; a long last row is left to the malformed share), with a test for each arm, since a quoted field holding a line break lets a cut end at one. A new CSV source in `tools/differential/local_corpora.py` takes the same check, and its skip shares are tested at their shipped values, not only patched open for a small fixture.
+
 **Expected-failure tests use `@pytest.mark.xfail`** — the conftest parametrized fixture breaks `@unittest.expectedFailure`; always use `@pytest.mark.xfail` instead.
 
 **`lc()` strips leading and trailing periods** — `'M.D.'` → `'m.d'`, not `'md'` (interior periods are preserved). Shipped keys in `capitalization_exceptions` are dot-free, so lookups must also try `.replace('.', '')`; whatever key matches, its value is a case mask applied to the word as written, never substituted for it (#459).

docs/design/mechanisms.md

@@ -414,7 +414,7 @@ print(len(MAIDEN_MARKERS), 'members ->', len(cls), 'structural classes')"
 
 **How it works.** WATCH asks whether a change moved a name: a committed corpus, `snapshot.jsonl` and a test that fails, or a local corpus read with `snapshot.py --local`, which no CI run sees. SCORE asks whether the parser agrees with someone who knows the fields: a committed fields file and agreement record, read by `cldr_agreement.py` from the repository alone. COUNT asks how one word is used: a cached source behind a row of `tools/name_usage.py`, with only the counts cited. DERIVE asks what a shipped list should hold: a cached source and a script writing the vocabulary (`tools/zh_surnames.py`). SURVEY asks how people write whole names, and how OFTEN they write each shape: a cached local corpus (`tools/differential/local_corpora.py`).
 
-A second axis cuts across the jobs: whether the names are real or invented, labelled with fields or bare text, chosen or unselected. Every committed corpus is CHOSEN: invented to fill fields (CLDR, the conventions table, the rules examples), cataloged (GND), filtered to names whose every word aligns with a stated part (both Wikidata corpora, a filter that drops credentials and typos), or picked by someone testing or reporting a case (v1's test names in `corpus.jsonl`, the case-table rows in `corpus_cjk.jsonl` and `corpus_shapes.jsonl`, and the strings reporters typed into `corpus_issues.jsonl`). The last group does hold hand-typed shapes — a job title in the name (`Bob Jones, author`), a credential before the comma (`Washington Jr. MD, Franklin`) — but one instance of each, as chosen. What SURVEY adds is the unselected population and its frequencies: ClinicalTrials.gov's study officials (local corpus `ctgov-officials`, measured 2026-10-21) are typed into a free-text field by sponsors' staff, so they show how often each shape occurs, and hold some no committed corpus does, such as `MBBS,FCPS` with no space. The FEC's individual contributors (local corpus `fec-individuals`, measured 2026-10-22) are unselected too, but mostly a filer's software writing a form's fields in a fixed order, so nearly all of its 1.89 million names share one shape (capitals, family, comma, given) and the hand-typed part is what goes inside the fields (a credential run or a suffix after a second comma): the population for that shape's variants, and blind to case. One source may do several jobs, each through its own code: Wikidata does COUNT live and WATCH and SCORE through its builders. A live source has no fixed file to pin, so its cached copy is the pin, carrying the source's own data date and a sha256 checked on every load (a truncated file otherwise reads as a run of false zeros, #775).
+A second axis cuts across the jobs: whether the names are real or invented, labelled with fields or bare text, chosen or unselected. Every committed corpus is CHOSEN: invented to fill fields (CLDR, the conventions table, the rules examples), cataloged (GND), filtered to names whose every word aligns with a stated part (both Wikidata corpora, a filter that drops credentials and typos), or picked by someone testing or reporting a case (v1's test names in `corpus.jsonl`, the case-table rows in `corpus_cjk.jsonl` and `corpus_shapes.jsonl`, and the strings reporters typed into `corpus_issues.jsonl`). The last group does hold hand-typed shapes — a job title in the name (`Bob Jones, author`), a credential before the comma (`Washington Jr. MD, Franklin`) — but one instance of each, as chosen. What SURVEY adds is the unselected population and its frequencies: ClinicalTrials.gov's study officials (local corpus `ctgov-officials`, measured 2026-10-21) are typed into a free-text field by sponsors' staff, so they show how often each shape occurs, and hold some no committed corpus does, such as `MBBS,FCPS` with no space. The FEC's individual contributors (local corpus `fec-individuals`, measured 2026-10-22) are unselected too, but mostly a filer's software writing a form's fields in a fixed order, so nearly all of its 1.89 million names share one shape (capitals, family, comma, given) and the hand-typed part is what goes inside the fields (a credential run or a suffix after a second comma): the population for that shape's variants, and blind to case. The UK Electoral Commission's individual donors (local corpus `ukec-individuals`, measured 2026-10-22) are the opposite shape: names as a donee's return gave them, mixed case and in spoken order, `parse()` reading a title in 8,219 of 15,214 (`Mr`, `Lord`, `Sir`) and only 2 holding a comma. One source may do several jobs, each through its own code: Wikidata does COUNT live and WATCH and SCORE through its builders. A live source has no fixed file to pin, so its cached copy is the pin, carrying the source's own data date and a sha256 checked on every load (a truncated file otherwise reads as a run of false zeros, #775).
 
 **Reach for it when.** A source is proposed, before choosing between a builder and a tool column; and when a corpus would hold real people's names nobody vetted for publication, which is the case for a local corpus rather than a committed one.