Papers with NIL prediction
Find the Funding: Entity Linking with Incomplete Funding Knowledge Bases (2022.coling-1)
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| Challenge: | Existing approaches to identifying and linking funding entities are suboptimal for the funding domain. |
| Approach: | They propose an entity linking model that can perform NIL prediction and overcome data scarcity issues in a time and data-efficient manner. |
| Outcome: | The proposed model outperforms existing baselines and overcomes data scarcity issues in a time and data-efficient manner. |
It’s All About the Confidence: An Unsupervised Approach for Multilingual Historical Entity Linking using Large Language Models (2026.eacl-long)
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| Challenge: | Existing approaches to EL for historical texts require substantial training data or rely on domain-specific rules that limit scalability. |
| Approach: | They propose an unsupervised ensemble approach combining a Small Language Model and an LLM for historical EL. |
| Outcome: | The proposed approach outperforms state-of-the-art models on four established benchmarks in six European languages from the 19th and 20th centuries. |
Learn to Not Link: Exploring NIL Prediction in Entity Linking (2023.findings-acl)
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| Challenge: | Entity linking models have been successful in capturing semantic features, but the NIL prediction problem has not been addressed. |
| Approach: | They propose an entity linking dataset that categorizes mentions linking to NIL into Missing Entity and Non-Entity Phrases. |
| Outcome: | The proposed dataset categorizes mentions linking to NIL into Missing Entity and Non-Entity Phrase categories and ensures the presence of mentions by human annotation and entity masking. |