We chose this approach since synthetic data generation can be especially useful in novel and early-stage research efforts, as it provides a controlled environment and allows for detailed analyses of a model's ability to solve a task.
while methods such as Recurrent Entity Networks have shown promise for keeping track of the state-of-the-world in our experiments, this is still in scenarios where the complexity of natural language is relatively simple.