# C3KG: A Chinese Commonsense Conversation Knowledge Graph

arXiv: https://arxiv.org/abs/2204.02549 · HTML: https://mlsanity.com/paper/2204.02549/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 35 references that are in the map.
- First posted on arXiv 6 Apr 2022.

## Builds on (most cited first, 22 of 22)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [ConceptNet 5.5: An Open Multilingual Graph of General Knowledge](https://mlsanity.com/paper/1612.03975/) (2016)
- [COMET: Commonsense Transformers for Automatic Knowledge Graph Construction](https://mlsanity.com/paper/1906.05317/) (2019)
- [COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs](https://mlsanity.com/paper/2010.05953/) (2020)
- [KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning](https://mlsanity.com/paper/1909.02151/) (2019)
- [COSMIC: COmmonSense knowledge for eMotion Identification in Conversations](https://mlsanity.com/paper/2010.02795/) (2020)
- [ASER: A Large-scale Eventuality Knowledge Graph](https://mlsanity.com/paper/1905.00270/) (2019)
- [Target-Guided Open-Domain Conversation](https://mlsanity.com/paper/1905.11553/) (2019)
- [Story Ending Generation with Incremental Encoding and Commonsense Knowledge](https://mlsanity.com/paper/1808.10113/) (2018)
- [Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs](https://mlsanity.com/paper/1911.02707/) (2019)
- [Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph](https://mlsanity.com/paper/2009.11692/) (2020)
- [TransOMCS: From Linguistic Graphs to Commonsense Knowledge](https://mlsanity.com/paper/2005.00206/) (2020)
- [A Taxonomy of Empathetic Response Intents in Human Social Conversations](https://mlsanity.com/paper/2012.04080/) (2020)
- [Commonsense for Generative Multi-Hop Question Answering Tasks](https://mlsanity.com/paper/1809.06309/) (2018)
- [DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense Knowledge](https://mlsanity.com/paper/2101.00154/) (2021)
- [Incorporating Structured Commonsense Knowledge in Story Completion](https://mlsanity.com/paper/1811.00625/) (2018)
- [CARE: Commonsense-Aware Emotional Response Generation with Latent Concepts](https://mlsanity.com/paper/2012.08377/) (2020)
- [CIDER: Commonsense Inference for Dialogue Explanation and Reasoning](https://mlsanity.com/paper/2106.00510/) (2021)
- [Thinking Clearly, Talking Fast: Concept-Guided Non-Autoregressive Generation for Open-Domain Dialogue Systems](https://mlsanity.com/paper/2109.04084/) (2021)
- [Towards an Online Empathetic Chatbot with Emotion Causes](https://mlsanity.com/paper/2105.11903/) (2021)
- [Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark](https://mlsanity.com/paper/2109.01839/) (2021)
- [Chat More If You Like: Dynamic Cue Words Planning to Flow Longer Conversations](https://mlsanity.com/paper/1811.07631/) (2018)

## Built on by (most cited first, 8 of 8)

- [Recent Advances in Multimodal Affective Computing: An NLP Perspective](https://mlsanity.com/paper/2409.07388/) (2024)
- [KALM: Knowledge-Aware Integration of Local, Document, and Global Contexts for Long Document Understanding](https://mlsanity.com/paper/2210.04105/) (2022)
- [TikTalk: A Video-Based Dialogue Dataset for Multi-Modal Chitchat in Real World](https://mlsanity.com/paper/2301.05880/) (2023)
- [A New Dataset and Empirical Study for Sentence Simplification in Chinese](https://mlsanity.com/paper/2306.04188/) (2023)
- [Exploring & Exploiting High-Order Graph Structure for Sparse Knowledge Graph Completion](https://mlsanity.com/paper/2306.17034/) (2023)
- [CARE: Cognitive-reasoning Augmented Reinforcement for Emotional Support Conversation](https://mlsanity.com/paper/2510.05122/) (2025)
- [Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model](https://mlsanity.com/paper/2306.10241/) (2023)
- [DeepPsy-Agent: A Stage-Aware and Deep-Thinking Emotional Support Agent System](https://mlsanity.com/paper/2503.15876/) (2025)

## Abstract (arXiv)

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.