Beyond generating new ideas, a creative system often needs to be able to seek out new information to use as part of its knowledge base. We're going to look at how we might use a neural network to classify actor dialogue to predict who is speaking based on some input text (as inspired by Kassabgi, Walker, and others). This might be useful for a creative film critic architecture, an interactive chatbot or robot, or even a system that is generating its own dialogues (say, as part of a film script, book, or playable experience).  We will be using NLTK for this PQ. Some of you already have experience with NLTK from our prior assignments. NLTK stands for "Natural Language Toolkit", and is a well-known resource among researchers in natural language processing.