Fine-tuned T5 base model for use as a frame semantic parser in the Frame Semantic Transformer project. This model is trained on data from FrameNet 1.7.
Usage
This is meant to be used a part of Frame Semantic Transformer. See that project for usage instructions.
Tasks
This model is trained to perform 3 tasks related to semantic frame parsing:
- Identify frame trigger locations in the text
- Classify the frame given a trigger location
- Extract frame elements in the sentence
Performance
This model is trained and evaluated using the same train/dev/test splits from FrameNet 1.7 annotated corpora as used by Open Sesame.
Task | F1 Score (Dev) | F1 Score (Test) |
---|---|---|
Trigger identification | 0.78 | 0.74 |
Frame Classification | 0.91 | 0.89 |
Argument Extraction | 0.78 | 0.75 |
- Downloads last month
- 6,505
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.