In addition to technological superiority (functional value), attention to design superiority (semantic value) is increasing as a source of competitiveness of new products relative to competing products. In this research, we connect patent right data and design right data at the inventor / creator level, and quantitatively analyze corporate organizations related to design innovation. First, machine learning was performed on a classification model for name disambiguation of inventors / creators using patent right and design right applications to the Japan Patent Office. The training data was constructed using rare name information that is less likely to have the same problem. By interconnecting the inventors' and creators' identifiers estimated with the learned classification model, we identified design creators who also created the patent inventions. Next, using this information, the participation status of the design creator in the patent invention was organized by time series and design category. As a result, it was found that the division of innovative labor into invention activity and design activity is in progress. Furthermore, we confirmed that this division of labor is particularly advanced among major patent applicants. As background information, specialization and fragmentation of innovation activities, utilization of external designers and open innovation may be examples of progress influencing the process.