Named Entity Recognition Ner On Scierc
المقاييس
F1
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
اسم النموذج | F1 | Paper Title | Repository |
---|---|---|---|
SciBERT (SciVocab) | 67.57 | SciBERT: A Pretrained Language Model for Scientific Text | |
SciBERT (Base Vocab) | 65.24 | SciBERT: A Pretrained Language Model for Scientific Text | |
SpERT | 70.33 | Span-based Joint Entity and Relation Extraction with Transformer Pre-training | |
Ours: cross-sentence | 68.2 | A Frustratingly Easy Approach for Entity and Relation Extraction | |
SCIIE | 64.20 | Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction | |
RDANER | 68.96 | A Robust and Domain-Adaptive Approach for Low-Resource Named Entity Recognition | |
SciDeBERTa v2 | 72.4 | SciDeBERTa: Learning DeBERTa for Science Technology Documents and Fine-Tuning Information Extraction Tasks |
0 of 7 row(s) selected.