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arXiv:2004.04100 · 中英对照阅读

KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation

Hao Zhou Thanks: Equal contribution Chujie Zheng Kaili Huang Minlie Huang Thanks: Corresponding author: Minlie Huang. Xiaoyan ZhuConversational AI Group, AI Lab., Dept. of Computer Science, Tsinghua UniversityBeijing National Research Center for Information Science and Technology,

中文速览

人类式知识对话常受限于缺少既有多轮交流、又标注知识关联的多主题数据,KdConv因此构建了一个中文知识驱动对话数据集,覆盖电影、音乐和旅游三个领域。研究者先整理领域知识图谱,再由双方都能查阅知识的标注者进行无预设目标的多轮聊天,并为每句话标注相关知识事实,同时鼓励自然切换话题。数据集包含约4500段对话和8.6万条话语,平均每段19轮,话题可在1至4个之间深入转换;基准实验显示,引入背景知识能提升生成和检索模型的表现,但现有模型仍难以维持知识连贯性,且不同领域效果差异明显。它的重要性在于为多轮知识规划、知识衔接以及跨领域迁移研究提供了更贴近真实交流的中文数据和统一评测基础。

摘要

The research of knowledge-driven conversational systems is largely limited due to the lack of dialog data which consist of multi-turn conversations on multiple topics and with knowledge annotations. In this paper, we propose a Chinese multi-domain knowledge-driven conversation dataset, KdConv, which grounds the topics in multi-turn conversations to knowledge graphs. Our corpus contains 4.5K conversations from three domains (film, music, and travel), and 86K utterances with an average turn number of 19.0. These conversations contain in-depth discussions on related topics and natural transition between multiple topics. To facilitate the following research on this corpus, we provide several benchmark models. Comparative results show that the models can be enhanced by introducing background knowledge, yet there is still a large space for leveraging knowledge to model multi-turn conversations for further research. Results also show that there are obvious performance differences between different domains, indicating that it is worth to further explore transfer learning and domain adaptation. The corpus and benchmark models are publicly available11 1 https://github.com/thu-coai/KdConv.

术语表

knowledge-driven conversational system
知识驱动型对话系统
KdConv
KdConv
multi-domain conversation dataset
多领域对话数据集
multi-turn conversation
多轮对话
knowledge annotation
知识标注
knowledge graph
知识图谱
benchmark model
基准模型
background knowledge
背景知识
knowledge-grounded conversation
知识支撑型对话
knowledge interaction
知识交互
knowledge planning
知识规划
knowledge grounding
知识关联
knowledge adaptation
知识适配
topic transition
主题转移
open-domain conversational system
开放域对话系统
task-oriented dialog system
面向任务的对话系统
slot-value pair
槽位-值对
knowledge resource
知识资源
structured knowledge graph
结构化知识图谱
unstructured text
非结构化文本
retrieval-based conversational model
检索式对话模型
generation-based conversational model
生成式对话模型
domain adaptation
领域适配
transfer learning
迁移学习
named entity recognition (NER)
命名实体识别(NER)
Wizard of Wikipedia (WoW)
Wizard of Wikipedia(WoW)
OpenDialKG
OpenDialKG
DuConv
DuConv