BE
nlpcl-lab/bert-event-extraction
Pytorch Solution of Event Extraction Task using BERT on ACE 2005 corpus
342 52 +0/wk
GitHub
ace2005 bert event-extraction pytorch
Trend
0
Star & Fork Trend (20 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
nlpcl-lab/bert-event-extraction has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | bert-event-extraction | Diffusion-BERT | gpl | slide-deck-ai |
|---|---|---|---|---|
| Stars | 342 | 341 | 341 | 344 |
| Forks | 52 | 28 | 38 | 54 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | Apache-2.0 | Apache-2.0 | MIT |
Capability Radar vs Diffusion-BERT
bert-event-extraction
Diffusion-BERT
Maintenance Activity 0
Last code push 2299 days ago.
Community Engagement 76
Fork-to-star ratio: 15.2%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.