I was trying to replicate the results for the one shot setting but not sure which sentences are used in the training set. Can you release the data preprocessing script for the 1-shot setting?
or
is it just following the order of the dataset and remove the sentences with replicated predicate sense?
Thank you.

I was trying to create a new conda env with the command
conda env create -f environment.yml, but I am getting ResolvePackageNotfound for some of the packages.
I googled on it but didn't find a concrete solution. Please help me resolve the issue

Hi,

Can you point me to the alignment? thank you!
I was wondering do you have alignment/mapping of argument roles across languages?

I was trying to run the evaluation script for cz and I got this error.

python evaluate_conll2009.py --scorer scorer_conll2009.pl --processor xlmr_ft_full_all/processor_config.json --model xlmr_ft_full_all/checkpoint_epoch=026-val_f1=0.9028.ckpt --config ../config/full/cz_config.json --output_dir xlmr_ft_full_all/

Evaluation on CZ

Traceback (most recent call last):
  File "evaluate_conll2009.py", line 114, in <module>
    if output_senses[i] != '_':
IndexError: list index out of range

other languages work fine. not sure what happened to this one.

Hello,

I would like to clarify the model architecture being used here. I thought this code performed predicate identification, predicate sense disambiguation, argument identification and argument classification in a single forward pass, but it looks like the "forward" function takes the indices of the predicate already identified as input. ie, see line 94 of srl/models/model.py.

I was hoping to emulate this model architecture for a similar task, but can't figure out how you go about predicate identification. Is the predicate identified before you encode and decode the sense and predicate-argument representations? If so, how?

Many thanks