The ProfessionAl Go annotation datasEt (PAGE)

TL;DR

The PAGE dataset offers a comprehensive collection of over 98,000 professional Go games with detailed AI analysis and metadata, enabling large-scale research into human gameplay and AI-human interactions.

Contribution

This paper introduces the first extensive annotated Go dataset, PAGE, including AI analysis, metadata, and potential applications for research and AI development.

Findings

Contains 98,525 professional games spanning 70 years

Includes rich AI move analysis for each game

Facilitates multiple research directions in Go AI and human play

Abstract

The game of Go has been highly under-researched due to the lack of game records and analysis tools. In recent years, the increasing number of professional competitions and the advent of AlphaZero-based algorithms provide an excellent opportunity for analyzing human Go 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. The dataset includes rich AI analysis results for each move. Moreover, PAGE provides detailed metadata for every player and game after manual cleaning and labeling. Beyond the preliminary analysis of the dataset, we provide sample tasks that benefit from our dataset to demonstrate the potential application of PAGE in multiple research directions. 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 application.