# Finding entities in language

Canonical URL: http://localhost:3000/research/entity-extraction
Published: 2026-09-22
Updated: 2026-09-22
Language: en

Research context for the University of Auckland internship.


## Motivation

Extracting and classifying entities is one way to turn unstructured text into information that software can work with.

## Approach

The University of Auckland research internship involved natural-language processing, entity extraction, and classification using CLAVIN and Stanford NER.

## What was built

The public record establishes work with these tools and tasks. A detailed account of the dataset and implementation has not yet been added.

## Results

No verified numerical results are included in this archive.

## Open questions

A fuller note can describe the entity categories, ambiguity cases, and evaluation approach once the source material is available.

## References

Exact dates, research artifacts, and references remain to be added.