Exploring Cross-sentence Contexts for Named Entity Recognition with BERT (2020.coling-main)
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| Challenge: | Named entity recognition (NER) is often addressed as a sequence classification task with each input consisting of one sentence of text. |
| Approach: | They propose a method to combine different predictions from multiple sentences in input samples to increase NER performance. |
| Outcome: | The proposed method improves on the state-of-the-art NER results on English, Dutch, and Finnish and achieves the best reported BERT-based results on German. |
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| Challenge: | Recent work shows document-level contexts can significantly improve Named Entity Recognition models. |
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Named Entity Recognition in Multi-level Contexts (2020.aacl-main)
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| Challenge: | Existing methods for named entity recognition are unsatisfactory for recognizing entities in limited or ambiguous sentence-level contexts. |
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| Challenge: | Existing methods to enhance BERT with factual knowledge about entities require no additional pretraining and no changes to the encoder itself. |
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| Challenge: | Named Entity Recognition (NER) is a fundamental and widely used task in natural language processing. |
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The Role of Global and Local Context in Named Entity Recognition (2023.acl-short)
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| Challenge: | Named Entity Recognition (NER) models are usually applied sequentially because of their complexity. |
| Approach: | They explore the impact of global document context on Named Entity Recognition . they find that correctly retrieving global document contextual has a greater impact . |
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Document-Level Neural Machine Translation Using BERT as Context Encoder (2020.aacl-srw)
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| Challenge: | Large-scale pre-trained representations such as BERT have been widely used in many natural language understanding tasks. |
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Sentence-Level Resampling for Named Entity Recognition (2022.naacl-main)
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| Challenge: | named entity recognition (NER) tasks are often dominated by the majority of non-entity tokens in text . a data imbalance problem is causing the NER models to ignore named entities . |
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