Implementing a Logical Inference System for Japanese Comparatives
This work addresses a domain-specific problem for Japanese language processing, but it is incremental as it adapts existing logical approaches from English to Japanese.
The study tackled the challenge of Natural Language Inference for Japanese comparatives by proposing ccg-jcomp, a logic-based system, and demonstrated its effectiveness with accuracy comparisons against existing Large Language Models.
Natural Language Inference (NLI) involving comparatives is challenging because it requires understanding quantities and comparative relations expressed by sentences. While some approaches leverage Large Language Models (LLMs), we focus on logic-based approaches grounded in compositional semantics, which are promising for robust handling of numerical and logical expressions. Previous studies along these lines have proposed logical inference systems for English comparatives. However, it has been pointed out that there are several morphological and semantic differences between Japanese and English comparatives. These differences make it difficult to apply such systems directly to Japanese comparatives. To address this gap, this study proposes ccg-jcomp, a logical inference system for Japanese comparatives based on compositional semantics. We evaluate the proposed system on a Japanese NLI dataset containing comparative expressions. We demonstrate the effectiveness of our system by comparing its accuracy with that of existing LLMs.