Papers with EL system

2 papers
ELDEN: Improved Entity Linking Using Densified Knowledge Graphs (N18-1)

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Challenge: Entity Linking (EL) systems aim to automatically map mentions of an entity in text to the corresponding entity in Knowledge Graph (KG).
Approach: They propose to densify the Knowledge Graph (KG) with co-occurrence statistics and then use the densified KG to train entity embeddings.
Outcome: The proposed system outperforms state-of-the-art EL systems on benchmark datasets and outperformed state- of-the art systems on sparsely connected entities in the KG.
Named Entity Recognition for Entity Linking: What Works and What’s Next (2021.findings-emnlp)

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Challenge: Entity Linking (EL) systems have achieved impressive results on standard benchmarks thanks to the contextualized representations provided by recent pretrained language models.
Approach: They propose to exploit Named Entity Recognition (NER) to narrow the gap between EL systems trained on high and low amounts of labeled data.
Outcome: The proposed model can be exploited to narrow the gap between EL systems trained on high and low amounts of labeled data.

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