Entity Disambiguation On Aida Conll

Metrics

In-KB Accuracy

Results

Performance results of various models on this benchmark

Model Name	In-KB Accuracy	Paper Title	Repository
Global	92.22	Deep Joint Entity Disambiguation with Local Neural Attention	-
ReFinED	93.9	ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity Linking	-
KBED	90.4	Improving Entity Disambiguation by Reasoning over a Knowledge Base	-
DCA-SL (2019)(et al., [2019c])	94.64	Learning Dynamic Context Augmentation for Global Entity Linking	-
GENRE	93.3	Autoregressive Entity Retrieval	-
Chen et al. (2020) (et al, 2020)	93.54	Improving Entity Linking by Modeling Latent Entity Type Information	-
Fang et al. (2019) (et al., [2019e])	94.3	Joint Entity Linking with Deep Reinforcement Learning	-
NER4EL	92.5	Named Entity Recognition for Entity Linking: What Works and What’s Next
Hoffart et al.	82.29	Robust Disambiguation of Named Entities in Text	-
NTEE	94.7	Learning Distributed Representations of Texts and Entities from Knowledge Base	-
BERT-Entity-Sim (local & global) AIDA-B	-	Improving Entity Linking by Modeling Latent Entity Type Information	-
This work+CtxLSTMs+LDC+MPCM	94.0	Neural Cross-Lingual Entity Linking	-
Bootleg	-	Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation	-
DeepType	94.88	DeepType: Multilingual Entity Linking by Neural Type System Evolution	-
ELDEN	93.0	ELDEN: Improved Entity Linking Using Densified Knowledge Graphs
Le& Titov (2019) (Le and Titov, 2019)	89.66	Boosting Entity Linking Performance by Leveraging Unlabeled Documents	-
confidence-order	95.0	Global Entity Disambiguation with BERT	-
DCA-SL + Triples	94.94	Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models	-
Wikipedia2Vec-GBRT	93.1	Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation	-
Wikipedia2Vec	91.5	Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation	-

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