Original code used for the system presented on the IEA/AIE 2023 (IKEDMS). As we unfortunately cannot provide the original training data, this code can be seen as documentation to better understand the paper.
- We offer the scattered phrase matcher as a standalone spaCy component here: lavis-nlp/scaphra
- This model is the precursor to the e2e models of IRT1 and IRT2: Check out the latest model implementation here: lavis-nlp/irt2m
- The training configuration of the models presented in the paper can be found in
conf/models/symptax.v7/kgc3-ce-1.ymlconf/models/symptax.v7/kgc3-ns-1.yml
Entry points:
- Used model: CE: draug/models/models.py#L869
- Used model: NS: draug/models/models.py#L919
- Training data sampling strategies: draug/models/data.py
- Scattered text sampling: draug/homag/sampling.py#L143
If you find this work interesting, please consider a citation
Coming soon