Japanese Chess Commentary Corpus with Named Entity and Modality Annotation

Abstract

In recent years, there has been a surge of interest in the natural language processing related to the real world, such as symbol grounding, language generation, and nonlinguistic data search using natural language queries. We argue that shogi (Japanese chess) commentaries, which are accompanied by game states, are an interesting testbed for these tasks. A commentator refers not only to the current board state but also to the past and future moves, and yet such references can be grounded in the game tree, possibly with the help of modern game-tree search algorithms. In this paper, we build a shogi commentary corpus and augment it with a manual annotation of word segmentation, named entities, modality expressions, and event factuality. This corpus can be used to train a computer to identify words and phrases that signal factuality and to determine events with the said factuality, paving the way for grounding possible and counterfactual states.