Handling Date Expressions to Mitigate Factual Errors in Automatic Summarization of Assembly Minutes

Abstract

The Tokyo Metropolitan Assembly follows a batch questioning and answering format, where multiple questions are asked consecutively and answered collectively. Despite being available online, the minutes are often difficult to navigate when searching for specific answers. To address this issue, the Question Answering-2 task in NTCIR-17 QA Lab-PoliInfo-4 aimed to develop a system that automatically generates summaries of responses to user-input questions. However, the system built using the provided training data contained factual errors, particularly in numerical information such as years and months. This study addresses one cause of these errors—relative date representations—by aligning them with the date of the plenary session, thereby reducing inaccuracies. Furthermore, we manually evaluated the improved summaries and analyzed the types and patterns of factual errors.