I hope you are ok and healthy, I have two types of questions, theoretical, implementation
1- I want to know your idea how can I use word2sense for a specific corpus (A book with 7000 sentences) to add more semantic to my word vector or my custom NER
2- How should I implement, I followed this
but I lost a bit, aI could run this comment on my specific corpus
python -m prodigy sense2vec.teach data_merged_v22 C:/Users/moha/Documents/Models/s2v_old --seeds "since"
her I used "since " and was looking for other cue words related to causation, however, I know that you also used sense2vecto improve NER
I would be happy if you can give me some hints mainly how can I Training your own sense2vec vectors AND how can use it to add more sematic to my model