Multilingual Named Entity Recognition
12 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Multilingual Named Entity Recognition
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
alibaba-nlp/kb-ner
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SemEval (NAACL) 2022
Our system wins 10 out of 13 tracks in the MultiCoNER shared task.
Entities, Dates, and Languages: Zero-Shot on Historical Texts with T0
bigscience-workshop/historical_texts
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BigScience (ACL) 2022
In this work, we explore whether the recently demonstrated zero-shot abilities of the T0 model extend to Named Entity Recognition for out-of-distribution languages and time periods.
Endowing Language Models with Multimodal Knowledge Graph Representations
We use the recently released VisualSem KG as our external knowledge repository, which covers a subset of Wikipedia and WordNet entities, and compare a mix of tuple-based and graph-based algorithms to learn entity and relation representations that are grounded on the KG multimodal information.
IXA/Cogcomp at SemEval-2023 Task 2: Context-enriched Multilingual Named Entity Recognition using Knowledge Bases
ikergarcia1996/context-enriched-ner
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Named Entity Recognition (NER) is a core natural language processing task in which pre-trained language models have shown remarkable performance.
