Self-Cleaning: Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances (2024.findings-naacl)
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| Challenge: | Existing methods to train named entity recognition models on noisy data are expensive and time-intensive to accumulate. |
| Approach: | They propose to denoise noisy NER data with guidance from a small set of clean instances. |
| Outcome: | The proposed method can improve on large-scale datasets with a small guidance set. |
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| Challenge: | Existing named entity recognition systems rely on large amounts of human-labeled data for supervision, but the result is noisy. |
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| Challenge: | Named entity recognition (NER) is a method of detecting entity spans and classifying them into predefined categories. |
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