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OneRel: Joint Entity and Relation Extraction with One Module in One Step
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use OneRel's fine-grained triple classifier and relation-specific horns tagging instead of PRGC | Joint entity and relation extraction · NYT* test (Partial Match) | F1: 92.6 -> 92.8 | Helped |
| Use OneRel's fine-grained triple classifier and relation-specific horns tagging instead of SPN | Joint entity and relation extraction · WebNLG* test (Partial Match) | F1: 93.4 -> 94.3 | Helped |
| Use OneRel's fine-grained triple classifier and relation-specific horns tagging instead of PRGC | Joint entity and relation extraction · NYT test (Exact Match) | F1: 92.7 -> 92.9 | Helped |
| Use OneRel's fine-grained triple classifier and relation-specific horns tagging instead of PRGC | Joint entity and relation extraction · WebNLG test (Exact Match) | F1: 88.5 -> 91.0 | Helped |
| Use the OneRel scoring classifier rather than a linear classifier over token and relation representations (ablation) | OneRel · NYT* test (Partial Match) | F1: 90.9 -> 92.8 | Helped |
| Use the OneRel scoring classifier rather than a linear classifier over token and relation representations (ablation) | OneRel · WebNLG* test (Partial Match) | F1: 92.6 -> 94.3 | Helped |
| Use the OneRel scoring classifier rather than a linear classifier over token and relation representations (ablation) | OneRel · NYT test (Exact Match) | F1: 90.8 -> 92.9 | Helped |
| Use the OneRel scoring classifier rather than a linear classifier over token and relation representations (ablation) | OneRel · WebNLG test (Exact Match) | F1: 89.4 -> 91.0 | Helped |
Closest papers by meaning
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