Generating Natural Language Retellings from Prom Week Play Traces

Because they have massive state spaces, authorial burden is especially pronounced in games that are underpinned by rich simulations; as such, this class of games represents perhaps the strongest use case for procedural content generation. In this paper, we outline ongoing work in which we procedurally generate natural language retellings of playthroughs of the social-simulation game Prom Week. We do this by parsing play trace files to create semantic encodings, which are then passed to an existing surface realizer that produces the retellings. Herein, we provide illustration and discussion of our methods as well as an evaluation of the retellings. While our work here concerns a specific game, we envision farreaching implications: if a game engine can produce natural language describing what has happened in the world, then content such as in-game journals, quest logs, histories, and even character dialogue may be generated automatically.