Economy Watchers Survey Provides Datasets and Tasks for Japanese Financial Domain
This addresses a gap in NLP resources for the Japanese financial domain, but it is incremental as it primarily introduces new datasets rather than novel methods.
The authors tackled the lack of Japanese financial NLP tasks by developing two large datasets from a Japanese government agency, providing three classification tasks including sentence categorization and sentiment analysis, with an automatic update framework to keep the datasets current.
Natural language processing (NLP) tasks in English and general domains are widely available and are often used to evaluate pre-trained language models. In contrast, fewer tasks are available for languages other than English and in the financial domain. Particularly, tasks in the Japanese and financial domains are limited. We develop two large datasets using data published by a Japanese central government agency. The datasets provide three Japanese financial NLP tasks, including 3- and 12-class classifications for categorizing sentences, along with a 5-class classification task for sentiment analysis. Our datasets are designed to be comprehensive and updated by leveraging an automatic update framework that ensures that the latest task datasets are publicly always available.