Universal NER

Universal Named Entity Recognition (UNER) aims to fill a gap in multilingual NLP: high quality NER datasets in many languages with a shared tagset.

UNER is modeled after the Universal Dependencies project, in that it is intended to be a large community annotation effort with language-universal guidelines. Further, we use the same text corpora as Universal Dependencies.

Universal NER v1

We are excited to release Universal NER v1. Here are the relevant links:

• Harvard Dataverse for official release: https://doi.org/10.7910/DVN/GQ8HDL
• Github repos for bleeding edge datasets: https://github.com/UniversalNER
• The paper, accepted to NAACL 2024.
• Huggingface dataset: Coming soon

Contributing

Are you interested in annotating or organizing? We need your help! Please join our discord!