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A Japanese Chess Commentary Corpus LREC 2016

In recent years there has been a surge of interest in the natural language prosessing related to the real world, such as symbol grounding, language generation, and nonlinguistic data search by natural language queries. …...

Annotating Event Appearance for Japanese Chess Commentary Corpus LREC 2020

In recent years, there has been a surge of interest in natural language processing related to the real world, such as symbol grounding, language generation, and non-linguistic data search by natural language queries. …...

Annotating Modality Expressions and Event Factuality for a{Japanese Chess Commentary Corpus LREC 2018

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 by natural language queries. …...

Aspect-based Sentiment Evaluation of Chess Moves (ASSESS): an NLP-based Method for Evaluating Chess Strategies from Textbooks LREC 2024

The chess domain is well-suited for creating an artificial intelligence (AI) system that mimics real-world challenges, including decision-making. Throughout the years, minimal attention has been paid to investigating …...

Detection and labeling of bad moves for coaching go CIG 2016

The level of computer programs has now reached professional strength for many games, even for the game of Go recently. A more difficult task for computer intelligence now is to create a program able to coach human …...

Enhancing Commentary Strategies for Imperfect Information Card Games: A Study of Large Language Models in Guandan Commentary Arxiv 2023

Recent advancements in large language models (LLMs) have unlocked the potential for generating high-quality game commentary. However, producing insightful and engaging commentary for complex games with incomplete …...

Learning a game commentary generator with grounded move expressions CIG 2015

This paper describes a machine learning-based approach for generating natural language comments on Shogi games. We generate comments by using a discriminative language model trained with a large amount of Shogi game …...

Learning to Generate Move-by-Move Commentary for Chess Games from Large-Scale Social Forum Data ACL 2018

This paper examines the problem of generating natural language descriptions of chess games. We introduce a new large-scale chess commentary dataset and propose methods to generate commentary for individual moves in a …...

SentiMATE: Learning to play Chess through Natural Language Processing Arxiv 2019

We present SentiMATE, a novel end-to-end Deep Learning model for Chess, employing Natural Language Processing that aims to learn an effective evaluation function assessing move quality. This function is pre-trained on …...

Understanding Game-Playing Agents with Natural Language Annotations ACL 2022

We present a new dataset containing 10K human-annotated games of Go and show how these natural language annotations can be used as a tool for model interpretability. Given a board state and its associated comment, our …...