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
- Huggingface dataset: Coming soon
Are you interested in annotating or organizing? We need your help! Please fill out this interest form.