What is state-of-the-art approach for negation scope detection using rule-based method in english? Exclude language other than english?
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The state-of-the-art approach for negation scope detection in English using a rule-based method is not mentioned in the provided abstracts.
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|---|---|
21 Citations | The state-of-the-art approach for negation scope detection in English is the proposed RecurCRFs model, which outperforms the current best models in terms of performance. |
Open access•Proceedings Article 01 May 2020 | The state-of-the-art approach for negation scope detection in English is NegBERT, which uses transfer learning with BERT and achieves high F1 scores on multiple datasets. |
Open access•Posted Content | The state-of-the-art approach for negation scope detection in English is NegBERT, which uses transfer learning with BERT and achieves high F1 scores on multiple datasets. |
| The state-of-the-art approach for negation scope detection in English is a transformer-based learning model with a BiLSTM-CRF sequence classification layer. | |
17 Citations | The paper does not mention any state-of-the-art approach for negation scope detection using a rule-based method in English. |
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