Lifelogging has gained more attention due to its wide applications, such as personalized recommendations or memory assistance. The issues of collecting and extracting personal life events have emerged. People often share their life experiences with others through conversations. However, extracting life events from conversations is rarely explored. In this paper, we present Life Event Dialog, a dataset containing fine-grained life event annotations on conversational data. In addition, we initiate a novel conversational life event extraction task and differentiate the task from the public event extraction or the life event extraction from other sources like microblogs. We explore three information extraction (IE) frameworks to address the conversational life event extraction task: OpenIE, relation extraction, and event extraction. A comprehensive empirical analysis of the three baselines is established. The results suggest that the current event extraction model still struggles with extracting life events from human daily conversations. Our proposed life event dialog dataset and in-depth analysis of IE frameworks will facilitate future research on life event extraction from conversations.

本文介绍 Life Event Dialog 数据集，并提出了基于对话数据的新型对话生活事件提取任务，对前沿的三种信息抽取方法（OpenIE、关系抽取和事件抽取）的表现进行了综合实证分析，说明目前的事件抽取模型仍然难以从人类日常对话中提取生活事件。希望我们提出的 Life Event Dialog 数据集和深入分析的信息抽取框架能够为未来的对话生活事件提取研究提供帮助。

对话生活事件抽取数据集LED