Overview
What this challenge is about.
Build an NER and entity-linking pipeline for 12,000 climate policy PDFs, evaluate against a benchmark, and publish Linked Data. Get a verifiable certificate.
The Brief
What you'll do, and what you'll demonstrate.
Link a 12,000-document climate-policy corpus to Wikidata and EuroVoc with measured precision and recall, and publish it as Linked Open Data.
Earning criteria — what you'll demonstrate
- Build an end-to-end entity-linking pipeline against Wikidata and EuroVoc
- Apply Linked Data publishing principles (URIs, sameAs, attribution)
- Evaluate entity-linking quality at precision/recall level
- Author methodology notes appropriate to grant-reporting expectations
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career paths this builds toward
Canonical rolesData Engineer
Publishing a corpus as Linked Open Data with measured linking quality is the day-to-day of data engineers at research and open-data orgs.
This challenge sharpens
- linked-open-data
- rdf
- entity-linking
NLP Engineer
NER plus disambiguation against a real KG is core NLP-engineer work in any entity-linking product.
This challenge sharpens
- ner
- entity-linking
- wikidata
AI Solutions Architect
Specifying the linked-data architecture and the publishing pipeline is the AI solutions architect's role in open-data engagements.
This challenge sharpens
- linked-open-data
- rdf
- sparql