Annotating Entity and Causal Relationships on Japanese Vehicle Recall Information

A vehicle recall system is a process of recall-ing and repairing vehicles with defective de-signs or potential for accidents and failures. The recall document concisely explains the circumstances and causes of product defects. This paper presents two types of annotations on public vehicle recall reports, part entities and their relations, and causality. We annotated 6,394 car-recall text documents. Named entity and relation annotation suggests a relationship between the elements of an auto-mobile, and causality annotation indicates the cause of a malfunction. The entity and relation annotation and causality annotation allow the system to automatically extract knowledge in the automotive design domain. Subsequently, we present the experimental results for named entity recognition and relation extraction and causality extraction of our annotated corpus to verify the feasibility of building a system for extracting part information and causality. Fi-nally, the experimental results show that employing named entity and relation information as the external knowledge improves causality extraction.