Photo by Patrick Tomasso on Unsplash

You want your AI agent to understand places; ports, roads, buildings, construction sites. OpenStreetMap is the obvious source. But feeding raw OSM data to an agent is like giving someone a raw database dump and asking for insights. It's possible, but painful.

We spent the last few weeks building a pipeline that turns OSM into clean RDF knowledge graphs. It's not a polished product; it's a working prototype that taught us a lot. This post shares the important steps, the mistakes we made, and the code that actually works.

What you'll get from this post:

Why bash scripts fail silently (and how to fix it)

How to generate RDF from OSM without losing your mind

A working Python pipeline you can adapt

Real examples from maritime and construction extraction

Let's dive in.

The problem with OSM + bash

Our first version was simple: a bash script that calls osmconvert to clip a region, then osmfilter to extract categories like transportation, buildings, and POIs.

Here's…