The script starts simply enough: A couple is at the end of dinner. Conversation winds down, the wine is almost finished. After a silence, the man says he wants to play a game. UsingGPT-3, we developed a short film script called Date Night. Tired of off-kilter AI like Cleverbot, we wanted to use more robust tech in our work.

The script starts simply enough: A couple is at the end of dinner. Conversation winds down, the wine almost finished. After a silence, the man says he wants to play a game. Using GPT-3, we developed a short film script called Date Night. Tired of off-kilter AI like Cleverbot, we wanted to use more robust tech in our work.

An exciting new script analysis product that uses artificial intelligence to help you understand your screenplay better. We at the Black List are big fans of technology and data. We believe that when interpreted correctly, they can provide critical and objective insights into the world. And since we're also passionate about giving writers tools to help them improve their work, we've partnered with ScriptBook on a new product, an artificial intelligence (AI) based script analysis tool that provides feedback to feature film writers on their scripts. ScriptBook is a technology company that uses machine learning and natural language processing to learn about film scripts.

We model anomaly and change in data by embedding the data in an ultrametric space. Taking our initial data as cross-tabulation counts (or other input data formats), Correspondence Analysis allows us to endow the information space with a Euclidean metric. We then model anomaly or change by an induced ultrametric. The induced ultrametric that we are particularly interested in takes a sequential - e.g. temporal - ordering of the data into account. We apply this work to the flow of narrative expressed in the film script of the Casablanca movie; and to the evolution between 1988 and 2004 of the Colombian social conflict and violence.

We study two aspects of information semantics: (i) the collection of all relationships, (ii) tracking and spotting anomaly and change. The first is implemented by endowing all relevant information spaces with a Euclidean metric in a common projected space. The second is modelled by an induced ultrametric. A very general way to achieve a Euclidean embedding of different information spaces based on cross-tabulation counts (and from other input data formats) is provided by Correspondence Analysis. From there, the induced ultrametric that we are particularly interested in takes a sequential - e.g. temporal - ordering of the data into account. We employ such a perspective to look at narrative, "the flow of thought and the flow of language" (Chafe). In application to policy decision making, we show how we can focus analysis in a small number of dimensions.

We analyze the style and structure of story narrative using the case of film scripts. The practical importance of this is noted, especially the need to have support tools for television movie writing. We use the Casablanca film script, and scripts from six episodes of CSI (Crime Scene Investigation). For analysis of style and structure, we quantify various central perspectives discussed in McKee's book, "Story: Substance, Structure, Style, and the Principles of Screenwriting". Film scripts offer a useful point of departure for exploration of the analysis of more general narratives. Our methodology, using Correspondence Analysis, and hierarchical clustering, is innovative in a range of areas that we discuss. In particular this work is groundbreaking in taking the qualitative analysis of McKee and grounding this analysis in a quantitative and algorithmic framework.