Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction (D19-1)
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| Challenge: | Existing studies on DS-based relation extraction (RE) methods focus on handling label noise, but other factors may have been overlooked. |
| Approach: | They propose a method to automatically adjust DS-RE models to a shifted label distribution problem . they find this problem exists in real-world DS datasets and can be overcome . |
| Outcome: | The proposed method achieves consistent performance gains on DS-trained models with an up to 23% relative F1 improvement, which verifies their assumptions. |
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