I have the natural language sentences as follows:
This is a black chair. It is next to the table.
Each phrase that represents an object is annotated with an object Id. For example, in the above sentence, we have:
This: 15, black chair: 15, It: 15, table: 14
(where, 14 and 15 are object Ids)
I would like to train a model to predict the object Id of each phrase representing an object for a new sentence. From what I understand, each training example will consist of the following structure:
Inputs: sentence + object phrase
Output: object id (from 18 available ids)
I would need to repeat the above for each object phrase in a sentence
My question: How do I prepare the training data for this task? How do I represent each object phrase (eg: 'black chair') and each sentence for training the neural network?