arXiv cs.AI· Miaozhe Lin, Qiongzheng Lin, Zhongwei Liang, Zijun Liu·· 1 天前AI 评分33
Causals：用于因果推理研究的开放知识图谱发布
Causals: An Open Knowledge Graph for Research on Causal Reasoning
AI 导读
Causals 是一个面向因果推理研究的开放知识图谱，初始版本基于新闻报道构建，包含 369,184 个节点和 1,272,418 条边，连接事件、组织、商品、金融工具等实体。该资源区分结构关系、观测与归因因果声明，并保留指向来源记录的链接，可用于研究语言模型如何检索相关上下文并将机制应用于具体事件。数据集以 CC BY 4.0 协议开放。
正文 · 原文
Abstract:Applying causal knowledge to a new event requires connecting the event to relevant entities and the relationships through which its consequences may unfold. We present Causals, an open knowledge graph for research on this form of reasoning. Its initial release, constructed from news reports, contains 369,184 nodes and 1,272,418 edges linking reported events, organizations, commodities, financial instruments, and other entities. Structural relationships, observations, and attributed causal claims retain distinct semantics and links to source records. We describe the construction and representation of the resource and characterize its connectivity and multi-hop retrieval properties. Causals provides shared relational knowledge for studying how language models retrieve relevant context and apply mechanisms to particular events. The dataset is available under CC BY 4.0 at this https URL, and we invite contributions to its ontology, records, and evidence.
| Comments: | 13 pages, 3 figures. Project website: this https URL |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2611.16267 [cs.AI] |
| (or arXiv:2611.16267v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2611.16267 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Miaozhe Lin [view email]
[v1]
Thu, 12 Nov 2026 04:13:29 UTC (38 KB)
来源：arXiv cs.AI · arxiv.org