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Aaron Po
2026-07-19 04:05:30 -04:00
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docs/pipeline/ETHICS-AND-KNOWN-ISSUES.md
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@@ -102,21 +102,19 @@ vendored verbatim, unmodified, from
(the `common-forenames-by-country.json` / `common-surnames-by-country.json`
release assets), released under **CC0** (public domain). That dataset's own
forename/surname lists are pulled from Wikipedia's "Lists of most common
surnames" and "List of most popular given names" as of the week of
2023-07-08 — see that project's README for full provenance. Names are not
LLM-generated; this is curated fixture data per ROADMAP.md §2. Per-forename
gender from the source data is preserved through to the sampled `Name`
(rather than discarded during loading) so it's available for gender-aware
persona/bio generation later.
surnames" and "List of most popular given names" as of the week of 2023-07-08 —
see that project's README for full provenance. Names are not LLM-generated; this
is curated fixture data per ROADMAP.md §2. Per-forename gender from the source
data is preserved through to the sampled `Name` (rather than discarded during
loading) so it's available for gender-aware persona/bio generation later.
The full multinational dataset is kept as-is (106 countries for forenames,
75 for surnames) rather than trimmed to `locations.json`'s current country
list, so it doesn't need re-sourcing if more countries are added later.
`SampleName()` (a free helper in `generate_users.cc`) returns no result for
a country present in neither file; of the countries in `locations.json`,
that's currently `KE`, `SE`, `SG`, `TH`, `VN`, and `ZA` — `GenerateUsers`
skips cities in those countries the same way brewery generation skips
cities whose enrichment lookup fails.
The full multinational dataset is kept as-is (106 countries for forenames, 75
for surnames) rather than trimmed to `locations.json`'s current country list, so
it doesn't need re-sourcing if more countries are added later. `SampleName()` (a
free helper in `generate_users.cc`) returns no result for a country present in
neither file; of the countries in `locations.json`, that's currently `KE`, `SE`,
`SG`, `TH`, `VN`, and `ZA` — `GenerateUsers` skips cities in those countries the
same way brewery generation skips cities whose enrichment lookup fails.
---
@@ -273,8 +271,7 @@ For languages such as Welsh (Wales), Māori (Aotearoa/New Zealand), or Sicilian
but is semantically incoherent. This comes from limited training-data coverage
rather than prompt engineering.
Output sample:
[./french-cities.example](french-cities.example)
Output sample: [./french-cities.example](french-cities.example)
#### Proposed Mitigations
@@ -298,9 +295,9 @@ curated real-world examples.
The generated code is **format-conformant by construction** — it always
satisfies the regex it was generated from — but it is not looked up from any
real postal registry. It does not correspond to a real address, business, or
resident, and should not be treated as accurate geocoding or delivery data.
This is consistent with the rest of the dataset: fixture data for a
proof-of-concept, not a source of truth.
resident, and should not be treated as accurate geocoding or delivery data. This
is consistent with the rest of the dataset: fixture data for a proof-of-concept,
not a source of truth.
---