I have a csv file with nearly 7000 names and 7000 student_IDs (in the format ex: OG69038). My model has two entities name and student_id. I used 10 names and 10 student_IDs from the data in the NLU training data and trained the model. I used “pretrained_embeddings_spacy” in the pipeline.
After training the model, it is predicting the name also as student_ID entity. Can some one help me with this? and also is there any way where I can train the NLU such that it can extract both the entities correctly?(for all the 7000)