I tried to ask in SO, but they told me to ask here.
I have a big dataset like this:
RELATION<tab>SENTENCE color<tab>The cat is black color<tab>My dog is white place<tab>Des Moines is in Iowa place<tab>Des Moines is the capital of Iowa is-a<tab>Des Moines is a city is-a<tab>3D printer is a type of printer is-a<tab>New Beetle was a car by Volkswagen ...
I need to build a classifier that, given a sentence, returns a relation as accurately as possible.
I have already programmed something with keras (python), but in this case I really don't know where to start from. For the moment I only realized that an important feature could be the order of the words in the sentence, but I don't know how to explot this.
Do you have some hint? E.g. about features, embeddings, hidden layers. May LSTM be a good NN? Why?
I hope this is not too broad, but I just need some hint.