SpanMarker for Multilingual Named Entity Recognition This is a SpanMarker model that can be used for multilingual Named Entity Recognition trained on the MultiNERD dataset. In particular, this SpanMarker model uses bert base multilingual cased as the underlying encoder. See train.py for the training script. Is your data not (always) capitalized correctly? Then consider using this uncased variant of this model by @lxyuan for better performance: lxyuan/span marker bert base multilingual uncased multinerd. Metrics Language Precision Recall F1 all 93.39 91.59 92.48 de 95.21 94.32 94.76 en 95.07 95.29 95.18 es 93.50 89.65 91.53 fr 93.86 90.07 91.92 it 91.63 93.57 92.59 nl 94.86 91.74 93.27 pl 93.51 91.83 92.66 pt 94.48 91.30 92.86 ru 93.70 93.10 93.39 zh 88.36 85.71 87.02 Label set Class Description Examples PER (person) People Ray Charles, Jessica Alba, Leonardo DiCaprio, Roger Federer, Anna Massey. ORG (organization) Associations, companies, agencies, institutions, nationalities and religious or political groups University of Edinburgh, San Francisco Giants, Google, Democratic Party. LOC (location) Physical locations (e.g. mountains, bodies of water), geopolitical entities (e.g. citie…
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