The Professional Go Annotation Dataset

Abstract

The field of Go game research is hampered by the absence of records and analytical tools. In recent years, the increasing number of professional competitions and the advent of AlphaZero-based algorithms provide an excellent opportunity for analyzing human games on a large scale. In this paper, we present the ProfessionAl Go annotation datasEt (PAGE), containing 98,525 games played by 2,007 professional players and spans over 70 years. PAGE incorporates both game-level metadata and in-game statistics across two dimensions. The game-level metadata pertinent to games, players, and tournaments is annotated by consolidating data from numerous reliable sources. The comprehensive in-game statistics are generated from the KataGo engine. Beyond the preliminary analysis of the dataset, we propose sample tasks that highlight PAGE's potential applications in various research areas. To the best of our knowledge, PAGE is the first dataset with extensive annotation in the game of Go. This work is an extended version of [1] where we perform a more detailed description, analysis, and applications.