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2026

Turn on geocoding without turning it into a project
666,000 addresses and not one country
We asked our address parser what it couldn't read
The model knew it was Austria. The resolver sent it to West Virginia.
We almost retrained a model to fix a stale symlink
We made Mailwoman speak Nominatim, and it put Warsaw in Indiana
A confidence you can route on
We lost to Nominatim in Europe. Then we found out why.
Right on the map, wrong on the test
We shipped 'world coverage.' It covered 97 countries.
243 round trips to find a city
843,000 postcodes and no Canada
Geocoding that never phones home
We keep the receipt on every coordinate
The provider registry meets the Universal Service Fund
Same building. Different company. Now what?
Three times this week, our metrics undersold us
The macro-F1 went up. Did the model get better?
A tie on Main Street, a rout at the PO Box
We built the fix for our worst weakness. Three gates made us earn it.
Match where it is, not how it's spelled
The autocomplete that couldn't finish a word
Can you fix order-blindness by turning up the volume?
One row crashed our corpus build. Twice, on the same character.
The model said P.O. Box all along. We just weren't listening.
Four numbers tried to lie to us in 24 hours. We shipped anyway.
A lookup table scored 100%. We shipped the model anyway.
The right name in the wrong state
We spent three retrains fixing a German bug that didn't exist
Which Berlin? When your metric grades the wrong thing
Which way does a postcode point?
The map runs out before the country does
Does a postcode know what country it's in?
Our parser fails 80% of our own tests. We shipped it anyway.
The model that never saw an intersection
Zero byte-fallback: a multi-script tokenizer from WOF-earth
Why Japanese addresses break Western parsers
PO Box Boîte Postale Apartado: Stage 3 ships with 6 new tags
FST gazetteer ships to the browser
Our model worked in CI but broke on every real device
Night Shift 2 — from thermal hangs to a shipped model in one session
Five tries, same failure — narrowing v0.5.0's training problem by elimination
Taming Who's On First — making sense of the world's open place data
Two voices arguing inside a model — a beginner-friendly debugging story
Four training runs, zero shipped weights — bisecting v0.5.0's divergence
Five training runs, one shipped checkpoint — what we learned from v0.4.0

Tags

A

Architecture8

C

Concepts1
Corpus pipeline7

E

Evaluation16

G

Geocoder hubris4
Geocoding18

I

Infrastructure8
International8

J

Japan (ja-JP)2

M

Methodology1
Model training17
Multi-locale1
Multilingual1

N

Neural classifier20
Night shift3
Non-Latin scripts1

O

Overture Maps1

P

Postcode components3
Project motivation5

R

Record matching4
Resolver / WOF14
Retrospective4
Rule + neural hybrid1
Rule-based classifiers1

T

Testing1

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