Yes, you can either train a model that recognizes both types at once or filter out the tags you don't want to be trained on.
On Thu, Jun 12, 2014 at 3:34 AM, Saurav Sharma <[email protected]> wrote: > Hi all, > > I am new to this realm (so I apologize for the n00bness) and had a question > regarding building the training set for NER Models. > > Let's say I want two models, one for finding Brands and one for finding > Weights. > > Would it be valid to have training data full of data that is double tagged? > > For example: > <START:brand> Pop-Tarts <END> Brown Sugar 12 pk <START:weight> 21 oz <END> > > I want to be able to identify the brands and weights. Can I use a set > filled with the above to train a model specifically for "brand", and then > use the same data to train for "weight"? > > Thanks in advance! >
