Construction and Analysis of Similarity-based Nikkei Company ID Linking System

Abstract

Nikkei Inc. owns newspapers focusing on the economy and the Nikkei company DB. By constructing an entity linking system to link company names in newspapers to the Nikkei company DB, it is expected application towards advanced information extraction related to specific companies. In this paper, we report the results of designing a Nikkei company ID linking system. Specifically, we created a dataset for linking company IDs to company names mentioned in Nikkei’s newspapers and implemented a pipeline system consisting of models for extracting company names from articles and linking them to company IDs. In experiments with the dataset, we confirmed superior linking performance compared to existing systems. Additionally, we organize the technical difficulties specific to company ID linking, and discuss the challenges of our system.