C3KG: A Chinese Commonsense Conversation Knowledge Graph

TL;DR

This paper introduces C3KG, a large-scale Chinese commonsense conversation knowledge graph that integrates social and dialog flow knowledge, and demonstrates its effectiveness through graph-conversation matching benchmarks.

Contribution

It creates the first Chinese commonsense conversation knowledge graph combining social and dialog flow knowledge, and develops a matching approach for graph-grounded conversational tasks.

Findings

Effective graph-conversation matching approach developed

Benchmark results show improved conversational task performance

First Chinese commonsense conversation knowledge graph

Abstract

Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational models to plan the next steps. To fill the gap, we curate a large-scale multi-turn human-written conversation corpus, and create the first Chinese commonsense conversation knowledge graph which incorporates both social commonsense knowledge and dialog flow information. To show the potential of our graph, we develop a graph-conversation matching approach, and benchmark two graph-grounded conversational tasks.