Research map / Large language models / Language, safety and interpretability
Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-Level Supervision
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| jointly infer entity links and relations instead of using hard external entity links | SNERL vs BRAN (Linker) · Full CTD test | F1: 30.5 -> 42.2 | Helped |
| jointly infer entity links and relations instead of using hard external entity links | SNERL vs BRAN (Linker) · Disease-phenotype test | F1: 8.3 -> 11.8 | Helped |
| jointly infer entity links and relations instead of using hard external entity links | SNERL vs BRAN (Linker) · BRAN-filtered CTD test | F1: 49.4 -> 49.7 | No clear effect |
| learn entity linking jointly rather than select the top string-match candidate | SNERL · CDR document-level entity linking | F1: 82.7 -> 86.6 | Helped |
| allow selection from the top 25 candidates rather than only the top candidate | entity-relation tuple prediction on CTD development set · CTD development set | tuple recall: 67.0% -> 80.0% | Helped |
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