Task-oriented Dialogue (TOD) Systems aim to build dialogue systems that
assist users in accomplishing specific goals, such as booking a hotel or a
restaurant. Traditional TODs rely on domain-specific APIs/DBs or external
factual knowledge to generate responses, which cannot accommodate subjective
user requests (e.g., "Is the WIFI reliable?" or "Does the restaurant have a
good atmosphere?"). To address this issue, we propose a novel task of
subjective-knowledge-based TOD (SK-TOD). We also propose the first
corresponding dataset, which contains subjective knowledge-seeking dialogue
contexts and manually annotated responses grounded in subjective knowledge
sources. When evaluated with existing TOD approaches, we find that this task
poses new challenges such as aggregating diverse opinions from multiple
knowledge snippets. We hope this task and dataset can promote further research
on TOD and subjective content understanding. The code and the dataset are
available at this https URL

本篇论文提出了主观知识为基础的任务导向对话系统（SK-TOD）的新任务，以及配套的数据集，该数据集包含了主观知识寻求对话上下文和手动注释的响应，并探究了多个知识片段的不同观点如何汇聚的问题，以期促进 TOD 和主观内容理解的进一步研究。