On the iOS version of our app we are using the Apple Word Tagger Model 20 so that it can assist us with parsing some complex sentences and that way we can extract the parts that we actually want. It is working fairly well.
I need something similar on Android.
Basically I would feed it a large sample of sentences and a classification for every word in the sentence and once it learns those I can pass it some new sentences and it’ll tell me the classification of each of the words.
A similar example to what we want would be an address parser. Imagine that the training data looks like:
123, house_number
E., direction_short
Main, street_name
Av., avenue
17123, house_number
W. direction_short
West, direction_long
Ct., court
10th, street_name
etc, etc
And then we pass it “87 W. Central St.”, then the word tagger would tell us 87 is house_number, W. is direction_short, etc.
I tried using the Bert Classifier and the NLClassifier with my own model but when I get the classifier results back it is analyzing the entire “87 W. Central St.” and telling me the score for each possible label, at least I think that is what is doing.
I need a model that will tell me the category (label) of each word in my sentence. Is there such a thing for Android?
Hope that makes sense.
Thanks.