Multilingual Named Entity Recognition

8 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised Features

ixa-ehu/ixa-pipe-nerc 31 Jan 2017

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 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 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 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 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.