I am using Stanford NER to recognize each entity in a search text. Once I identify entities, I need to pass that entities to an algorithm which calculates score for each entity type (e.g. country, customer) using weights of each word. Currently my training data has word and answer like below.country_training.tsv    brazil country    japan countrycustomer_training.tsv    hyundai customer    apple customerHow can i associate weight to each above training data like below so when I can get weight of each word too ?country_training.tsv    brazil country 1.5    japan country 4.0customer_training.tsv    hyundai customer 4.0    apple customer 2.3Please advice.Weights are input to NER to annotate each entity wiith their weights.
Stanford NER Training - Assign weight to each word
nlp;language model;stanford nlp