A slot value might be provided segment by segment over multiple-turn
interactions in a dialog, especially for some important information such as
phone numbers and names. It is a common phenomenon in daily life, but little
attention has been paid to it in previous work. To fill the gap, this paper
defines a new task named Sub-Slot based Task-Oriented Dialog (SSTOD) and builds
a Chinese dialog dataset SSD for boosting research on SSTOD. The dataset
includes a total of 40K dialogs and 500K utterances from four different
domains: Chinese names, phone numbers, ID numbers and license plate numbers.
The data is well annotated with sub-slot values, slot values, dialog states and
actions. We find some new linguistic phenomena and interactive manners in SSTOD
which raise critical challenges of building dialog agents for the task. We test
three state-of-the-art dialog models on SSTOD and find they cannot handle the
task well on any of the four domains. We also investigate an improved model by
involving slot knowledge in a plug-in manner. More work should be done to meet
the new challenges raised from SSTOD which widely exists in real-life
applications. The dataset and code are publicly available via
this https URL.

本文定义了新的 Sub-Slot 口语任务（SSTOD），并构建了一个用于该任务研究的中文对话数据集。数据集包括来自四个不同领域的 40K 对话和 500K 次话语，并用子时隙值、时隙值、对话状态和动作进行了良好的注释。我们在 SSTOD 上测试了三个最先进的对话模型，并发现它们无法很好地处理四个领域中的任何一个任务。我们还研究了一种通过插件方式涉及时隙知识的改进模型。SSTOD 中产生的新挑战需要更多的工作，因为它广泛存在于现实生活应用中。