I am somewhat a novice at the topic of Neural Netoworks and PyTorch.
I am trying to create a model that takes a word (that I have modified very slightly) and a 'window' of context around it and predicts one of 5 tags (the tags relate to what sort of action I should perform on that word to get its correct form).
For example, here's what I would call a window of size 7 and it's tag (what it means isn't too important, it's just the 'target'):
Sentence Label here is a sentence for my network N
sentence is the word that I want the network to predict the label for, but the 3 words on either side provide contextual meaning. My problem is, how would I get a network to know I want it to predict for that central word but not outright ignore the others? I am familiar with more normal NLP tasks such as NMT and character level classification.
I have already gotten my dataset 'padded' out so they're all of equal size.
Any help is appreciated