Multilingual Named Entity Recognition
8 papers with code • 0 benchmarks • 2 datasets
Benchmarks
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Libraries
Use these libraries to find Multilingual Named Entity Recognition models and implementations
XFUND
WikiNEuRal
Most implemented papers
Multilingual Named Entity Recognition Using Pretrained Embeddings, Attention Mechanism and NCRF
sberbank-ai/ner-bert
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WS 2019
In this paper we tackle multilingual named entity recognition task.
Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised Features
Finally, the results show that our emphasis on clustering features is crucial to develop robust out-of-domain models.
Tuning Multilingual Transformers for Named Entity Recognition on Slavic Languages
deepmipt/Slavic-BERT-NER
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Conference: Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing 2019
Our paper addresses the problem of multilingual named entity recognition on the material of 4 languages: Russian, Bulgarian, Czech and Polish.
Sequence Tagging with Contextual and Non-Contextual Subword Representations: A Multilingual Evaluation
bheinzerling/subword-sequence-tagging
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ACL 2019
Pretrained contextual and non-contextual subword embeddings have become available in over 250 languages, allowing massively multilingual NLP.
Tuning Multilingual Transformers for Language-Specific Named Entity Recognition
deepmipt/Slavic-BERT-NER
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WS 2019
Our paper addresses the problem of multilingual named entity recognition on the material of 4 languages: Russian, Bulgarian, Czech and Polish.
Sources of Transfer in Multilingual Named Entity Recognition
davidandym/multilingual-NER
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ACL 2020
However, a straightforward implementation of this simple idea does not always work in practice: naive training of NER models using annotated data drawn from multiple languages consistently underperforms models trained on monolingual data alone, despite having access to more training data.
DAMO-NLP at SemEval-2022 Task 11: A Knowledge-based System for Multilingual Named Entity Recognition
Our system wins 10 out of 13 tracks in the MultiCoNER shared task.
