  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.
