Building a corpus for Japanese wikification with fine-grained entity classes

Abstract

In this research, we build a Wikification corpus for advancing Japanese Entity Linking. This corpus consists of 340 Japanese newspaper articles with 25,675 entity mentions. All entity mentions are labeled by a fine-grained semantic classes (200 classes), and 19,121 mentions were successfully linked to Japanese Wikipedia articles. Even with the fine-grained semantic classes, we found it hard to define the target of entity linking annotations and to utilize the fine-grained semantic classes to improve the accuracy of entity linking.