Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text (2021.findings-emnlp)
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| Challenge: | Existing methods for named entity disambiguation are limited by coarse-grained structural resources in biomedical knowledge bases and training datasets that provide low coverage over uncommon resources. |
| Approach: | They propose a method that integrates structural knowledge from general text knowledge bases to the medical domain. |
| Outcome: | The proposed method improves disambiguation accuracy on two benchmark medical NED datasets by up to 57 points. |
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