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Entity Linking on AIDA (testa)

92.9Micro F1SPEL-large
38.352.47566.6580.825Oct 23, 2023

Evaluation results

MethodLinks
SPEL-largeCandidate Set=PPRforNED candidate set, context-mode=context-aware, #params on GPU=361.1M, speed sec/doc=0.2672023.1092.9
SPEL-baseCandidate Set=PPRforNED candidate set, context-mode=context-aware, #params on GPU=128.9M, speed sec/doc=0.1562023.1092.7
SPEL-largeCandidate Set=PPRforNED candidate set, context-mode=context-agnostic, #params on GPU=361.1M, speed sec/doc=0.2682023.1092
SPEL-baseCandidate Set=PPRforNED candidate set, context-mode=context-agnostic, #params on GPU=128.9M, speed sec/doc=0.1562023.1091.7
SPEL-largeCandidate set setting=no mention-specific, US$ for 1000 docs=2.642023.1091.6
SPEL-largeCandidate Set=no mention-specific candidate set, #params on GPU=361.1M, speed sec/doc=0.2732023.1091.6
SPEL-baseCandidate set setting=no mention-specific, US$ for 1000 docs=2.282023.1091.3
SPEL-baseCandidate Set=no mention-specific candidate set, #params on GPU=128.9M, speed sec/doc=0.0842023.1091.3
Poerner et al. (2020)Architecture=BERT, #params on GPU=131.1M2023.1090.8
SPEL-largeCandidate Set=KB+Yago candidate set, #params on GPU=361.1M, speed sec/doc=0.2672023.1090.8
SPEL-baseCandidate Set=KB+Yago candidate set, #params on GPU=128.9M, speed sec/doc=0.1582023.1090.6
De Cao et al. (2021a)Architecture=RoBERTa+LSTM, Candidate Set=using PPRforNED candidate set, #params on GPU=124.8M, speed sec/doc=0.1942023.1090.1
Kolitsas et al. (2018)Architecture=LSTM, #params on GPU=330.7M, speed sec/doc=0.0972023.1089.4
Broscheit (2019)Architecture=BERT, #params on GPU=495.1M, speed sec/doc=0.6132023.1086
Martins et al. (2019)Architecture=Stack-LSTM2023.1085.2
van Hulst et al. (2020)Architecture=LSTM, #params on GPU=19.0M, speed sec/doc=0.3372023.1083.3
Peters et al. (2019)Architecture=BERT2023.1082.1
Févry et al. (2020)Architecture=Transformer2023.1079.7
Hoffart et al. (2011)Architecture=Linear2023.1072.4
GPT-4.0Prompting strategy=few-shot w/ CoT, Candidate set setting=no mention-specific, US$ for 1000 docs=59.372023.1062.4
De Cao et al. (2021a)Architecture=RoBERTa+LSTM, Candidate Set=no mention-specific candidate set, #params on GPU=124.8M, speed sec/doc=0.2682023.1061.9
GPT-3.5Prompting strategy=zero-shot, Candidate set setting=no mention-specific, US$ for 1000 docs=4.222023.1047.3
GPT-4.0Prompting strategy=zero-shot, Candidate set setting=no mention-specific, US$ for 1000 docs=42.172023.1040.4