3 posts tagged with "Te reo Māori"

When people ask whether ChatGPT, Claude, Gemini, Llama, Qwen or DeepSeek has been trained on Māori material, the honest answer is more complicated than yes or no. The developers of current frontier models do not publish complete lists of every webpage, PDF, book, image or other item used during training. That means we cannot point to a current model and prove that it learned from a particular Waitangi Tribunal report or iwi website unless the developer has disclosed it.

But that does not mean we know nothing. We can inspect some of the large public web corpora that have fed the modern AI ecosystem. When we do that, Māori material is plainly there.

The most useful evidence comes from mC4, the multilingual version of Google’s C4 corpus built from Common Crawl. The publicly accessible Māori-language subset contains roughly 101,000 training records labelled mi. Those records include genuine Māori-language and Māori-related pages from Te Ara, Dictionary of New Zealand Biography material, Māori media, arts organisations and at least one iwi website. They also include classification errors and rubbish, so the number must not be misrepresented as 101,000 clean Māori documents. What it does prove is that Māori online material has already been swept into web-scale corpora used by the AI research community.

Local AI has become much more useful in 2026. A normal desktop computer can now run a capable language model, search a collection of PDFs, extract structured information, help write Python or QGIS expressions and keep the working material on the machine. That makes it particularly interesting for Māori GIS, where the question is often not only whether AI can do the work, but where the information goes while it is doing it.

The most useful local workflow is not a private version of ChatGPT that somehow knows everything about Māori GIS. It is more modest and, for research, more useful. Give the system documents you are allowed to work with. Ask it to find candidate information. Keep the original wording and source reference. Have a person review the result. Check any geographic match against an appropriate source. Only then let the reviewed information become GIS data.

That distinction matters. A language model is quite capable of reading a reference to an old kāinga, deciding what modern place it probably means and supplying coordinates that look perfectly respectable. A GIS will then plot those coordinates without showing the slightest concern about whether they were invented. Local AI changes where the mistake was made. It does not make the mistake authoritative.

The practical question is therefore: what can we now run locally, what is genuinely offline, what appears promising for te reo Māori, and where should AI stop before the map begins?

There is now a small new addition to Māori GIS Mapping: Kupu Matawhenua, a weekday five-letter word game made for the Ngā Poutama Matawhenua community and anyone else who spends too much time thinking about maps, whenua, taiao and GIS.

The idea is deliberately simple. You get six attempts to find a five-letter word. Some answers are familiar GIS terms such as LAYER, POINT or QUERY. Others are kupu Māori connected with the places, relationships, environmental themes and kinds of mahi that regularly appear in Māori GIS. The aim is not to turn te reo Māori into decoration around an English GIS game. The word set includes concepts such as marae, taiao, ingoa, rāhui, urupā, tūnga, pānga, kūrae, mauri and pūaha because they belong naturally in conversations about place and spatial work.

Tākaro ināianei / Play Kupu Matawhenua →