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Entity Disambiguation On Aida Conll

Metrics

In-KB Accuracy

Results

Performance results of various models on this benchmark

Paper Title
confidence-order95.0Global Entity Disambiguation with BERT
DCA-SL + Triples94.94Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models
DeepType94.88DeepType: Multilingual Entity Linking by Neural Type System Evolution
NTEE94.7Learning Distributed Representations of Texts and Entities from Knowledge Base
DCA-SL (2019)(et al., [2019c])94.64Learning Dynamic Context Augmentation for Global Entity Linking
Fang et al. (2019) (et al., [2019e])94.3Joint Entity Linking with Deep Reinforcement Learning
This work+CtxLSTMs+LDC+MPCM94.0Neural Cross-Lingual Entity Linking
ReFinED93.9ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity Linking
Chen et al. (2020) (et al, 2020)93.54Improving Entity Linking by Modeling Latent Entity Type Information
GENRE93.3Autoregressive Entity Retrieval
Wikipedia2Vec-GBRT93.1Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation
ELDEN93.0ELDEN: Improved Entity Linking Using Densified Knowledge Graphs
NER4EL92.5Named Entity Recognition for Entity Linking: What Works and What’s Next
Global92.22Deep Joint Entity Disambiguation with Local Neural Attention
Wikipedia2Vec91.5Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation
KBED90.4Improving Entity Disambiguation by Reasoning over a Knowledge Base
Le& Titov (2019) (Le and Titov, 2019)89.66Boosting Entity Linking Performance by Leveraging Unlabeled Documents
Hoffart et al.82.29Robust Disambiguation of Named Entities in Text
BERT-Entity-Sim (local & global) AIDA-B-Improving Entity Linking by Modeling Latent Entity Type Information
Bootleg-Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
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Entity Disambiguation On Aida Conll | SOTA | HyperAI