C3KG: A Chinese Commonsense Conversation Knowledge Graph
Dawei Li, Yanran Li, Jiayi Zhang, Ke Li, Chen Wei, Jianwei Cui, Bin Wang
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. All the resources in this work will be released to foster future research.- Anthology ID:
- 2022.findings-acl.107
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2022
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1369–1383
- Language:
- URL:
- https://aclanthology.org/2022.findings-acl.107
- DOI:
- 10.18653/v1/2022.findings-acl.107
- Cite (ACL):
- Dawei Li, Yanran Li, Jiayi Zhang, Ke Li, Chen Wei, Jianwei Cui, and Bin Wang. 2022. C3KG: A Chinese Commonsense Conversation Knowledge Graph. In Findings of the Association for Computational Linguistics: ACL 2022, pages 1369–1383, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- C3KG: A Chinese Commonsense Conversation Knowledge Graph (Li et al., Findings 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.findings-acl.107.pdf
- Code
- xiaomi/c3kg
- Data
- ATOMIC, ConceptNet, MOD