Improving Entity Disambiguation by Reasoning over a Knowledge Base (2022.naacl-main)
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| Challenge: | Recent work in entity disambiguation relies on a limited subset of KB facts to link entities . less common entities are prone to missing or inconsistent KB information, which is problematic for models which rely on 'one source' |
| Approach: | They propose an ED model which links entities by reasoning over a symbolic knowledge base in a fully differentiable fashion. |
| Outcome: | The proposed model outperforms state-of-the-art models on six well-established datasets by 1.3 F1 on average. |
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