Relation Extraction On Semeval 2010 Task 8
評価指標
F1
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
比較表
| モデル名 | F1 |
|---|---|
| representing-knowledge-by-spans-a-knowledge | 88.8 |
| reviewing-labels-label-graph-network-with-top | 90.5 |
| representing-knowledge-by-spans-a-knowledge | 89.2 |
| matching-the-blanks-distributional-similarity | 89.5 |
| adaprompt-adaptive-prompt-based-finetuning | 90.3 |
| knowledge-enhanced-contextual-word | 89.1 |
| representing-knowledge-by-spans-a-knowledge | 88.7 |
| improving-relation-extraction-by-pre-trained-1 | 87.1 |
| representing-knowledge-by-spans-a-knowledge | 90.6 |
| improving-relation-extraction-through-syntax | 89.90 |
| representing-knowledge-by-spans-a-knowledge | 89.1 |
| representing-knowledge-by-spans-a-knowledge | 90.3 |
| bidirectional-long-short-term-memory-networks | 82.7 |
| dependency-driven-relation-extraction-with | 89.85 |
| relation-extraction-as-two-way-span | 91.9 |
| classifying-relations-by-ranking-with | 84.1 |
| attention-based-convolutional-neural-network-2 | 84.3 |
| downstream-model-design-of-pre-trained | 91 |
| attention-based-bidirectional-long-short-term | 84.0 |
| relation-classification-via-multi-level | 88.0 |
| enhancing-relation-extraction-using-syntactic | 90.36 |
| generalizing-natural-language-analysis-1 | 87.4 |
| improving-relation-classification-by-entity | 90.2 |
| semantic-relation-classification-via-1 | 85.2 |
| improving-relation-extraction-by-pre-trained-1 | 87:1 |
| enriching-pre-trained-language-model-with | 89.25 |
| representation-iterative-fusion-based-on | 91.3 |
| sequence-generation-with-label-augmentation | 90.4 |
| extracting-multiple-relations-in-one-pass | 89.0 |
| relation-classification-via-convolutional | 82.7 |
| representing-knowledge-by-spans-a-knowledge | 89.4 |