In order to alleviate the shortage of multi-domain data and to capture
discourse phenomena for task-oriented dialogue modeling, we propose RiSAWOZ, a
large-scale multi-domain Chinese Wizard-of-Oz dataset with Rich Semantic
Annotations. RiSAWOZ contains 11.2K human-to-human (H2H) multi-turn
semantically annotated dialogues, with more than 150K utterances spanning over
12 domains, which is larger than all previous annotated H2H conversational
datasets. Both single- and multi-domain dialogues are constructed, accounting
for 65% and 35%, respectively. Each dialogue is labeled with comprehensive
dialogue annotations, including dialogue goal in the form of natural language
description, domain, dialogue states and acts at both the user and system side.
In addition to traditional dialogue annotations, we especially provide
linguistic annotations on discourse phenomena, e.g., ellipsis and coreference,
in dialogues, which are useful for dialogue coreference and ellipsis resolution
tasks. Apart from the fully annotated dataset, we also present a detailed
description of the data collection procedure, statistics and analysis of the
dataset. A series of benchmark models and results are reported, including
natural language understanding (intent detection & slot filling), dialogue
state tracking and dialogue context-to-text generation, as well as coreference
and ellipsis resolution, which facilitate the baseline comparison for future
research on this corpus.

本研究提出了 RiSAWOZ，这是一个大规模的、多领域的中文人机对话数据集，并提供了丰富的语义注释和对话自然语言描述，可用于对话系统的基准比较和未来研究的任务导向对话建模。