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 fill out this interest form.

If you want to receive news about Universal NER, you can subscribe to the UNER mailing list. If you want to discuss individual annotation questions, use the Github issue tracker.