Selecting Span Problem about spert HOT 2 CLOSED

My understanding from the code is that during training the system uses gold label spans and generates all negative spans, then does some downsampling for the negative spans (a hyperparameter). During inference/evaluation, however, it generates all possible spans and selects the best spans based on how the model prioritizing them i.e. what has it learned through the training. The authors might confirm this.
For the second question, that is exactly what this system does. You don't need pre-annotated entities or relation labels for inference. This is a 'relation extraction' task.

from spert.

Thanks for answering this issue @avipartho. You are right, during inference we classify all spans up to length 10 (this is a hyperparameter - you can adjust it in the config file). Any span assigned to the 'None' class is then filtered.

from spert.