Answering Game Rulebook Enquiries Through Natural Language Processing

Abstract: The aim of this research project was to create a conversationalinterface for retrieving information from rulebooks. This conversationalinterface takes the shape of an assistant named OLGA (shortfor Open Legend Game Assistant) to whom you can give enquiriesabout the rules of any game loaded into the program. We tunedand designed the assistant around a specic type of board gamescalled TRPGs (tabletop role playing games), hence the conversationalinterface is focused around game rulebooks. By giving theassistant the rules for a game in the form of a raw text documentthe program can extract key concepts and words from therules which we call entities. The process of extracting entities andall other functions of the assistant were calibrated on the TRPGcalled Open Legend, hence the name Open Legend Game Assistant.When the user sends a query to the assistant it is rst sentto the web service Dialog ow for interpretation. In Dialog owwe enter our extracted entities to assist the service in recognizingkey words and concepts in the queries. Dialog ow then returnsan object with information telling the assistant what the intentof the user's query was and any additional information provided.The assistant then responds to the query. The standard responsefor a request for information about an entity is what we call astreak search. The assistant locates parts of the rules that containthe entity and sorts them by a relevance score, then the resultsare presented in order of relevance. When testing on people withno prior knowledge of the game it was concluded that the assistantindeed could be helpful in nding answers to rule questions inthe limited amount of time provided. Generalization being one ofour goals the program was also applied on another rule system inthe TRPG genre, Pathnder, applied on this system the assistantworked as intended without altering any algorithm.