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Table 8 Span detection F1 score results for all algorithms tested against the core evaluation annotation set of the 30 held-out articles

From: Concept recognition as a machine translation problem

Ontology

CRF

BiLSTM

BiLSTM-CRF

Char-Embeddings

BiLSTM-ELMo

BioBERT

ChEBI

0.7234

0.6545

0.5000

0.5280

0.0620

0.9091*

CL

0.8333

0.5882

0.3774

0.8000

0.0000

0.9231*

GO_BP

0.8677*

0.5498

0.3661

0.6346

0.0685

0.8646

GO_CC

0.9412

0.1379

0.2689

0.2581

0.1000

0.9444*

GO_MF

> 0.9999*

> 0.9999*

> 0.9999*

0.8421

0.0000

> 0.9999*

MOP

> 0.9999*

> 0.9999*

> 0.9999*

> 0.9999*

0.0000

> 0.9999*

NCBITaxon

0.9959*

0.8551

0.9440

0.9569

0.0711

0.9453

PR

0.4351

0.2979

0.2151

0.0995

0.0339

0.8199*

SO

0.9435*

0.4935

0.4897

0.8203

0.1059

0.9081

UBERON

0.7913

0.7206

0.4758

0.7440

0.0854

0.8826*

  1. The best-performing algorithm per ontology is bolded with an asterisk*