Show HN：1 万个英语单词溯源自 4 大基础（空间、时间、能量、模式）
1 分•作者: sauronsrv•2 天前
将每个概念想象成坐落在由相关词语和想法构成的云团中。这张概念图谱只保留了关键的连接——也就是你首先需要理解的那些更简单的概念。沿着这些边向下追溯，每个概念最终都会落入四个基础之一：空间、时间、能量、模式。这条链的深度大致反映了该概念在涌现的层级结构中所处的位置。
在此搜索：[https://emergencemachine.com/atlas/search](https://emergencemachine.com/atlas/search)
你还可以比较两个概念的图，看看它们有哪些共同之处：[https://emergencemachine.com/atlas/distance](https://emergencemachine.com/atlas/distance)
每个概念也可以与网站的 AI——普罗米修斯进行讨论和辩论。
工具：Python (asyncpg + 自定义 DAG 遍历) 遍历了“概念”的先决条件图，直至其四个基础根节点，然后 Graphviz (dot 引擎) 渲染了 SVG。PostgreSQL 支持实时概念图谱；链式图像是确定性构建的。
阅读更多：[https://emergencemachine.com/language-emergent-tool/](https://emergencemachine.com/language-emergent-tool/)
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Think of each concept as sitting in a cloud of related words and ideas. The atlas keeps only the load-bearing connections — the simpler ideas you'd need to understand it first. Follow those edges down and every concept lands on one of four foundations: Space, Time, Energy, Pattern. The depth of that chain gives you a rough sense of where the concept sits in the emergent hierarchy.<p>Search here : <a href="https://emergencemachine.com/atlas/search" rel="nofollow">https://emergencemachine.com/atlas/search</a><p>You can also compare two concept's graph, see what they have in common- <a href="https://emergencemachine.com/atlas/distance" rel="nofollow">https://emergencemachine.com/atlas/distance</a><p>Each Concept can also be discussed and debated with site's AI- Prometheus.<p>Tool: Python (asyncpg + custom DAG traversal) walked the "concepts" prerequisite graph down to its four foundation roots, then Graphviz (dot engine) rendered the SVG. PostgreSQL backs the live atlas; the chain image is built deterministically.<p>Read more: <a href="https://emergencemachine.com/language-emergent-tool/" rel="nofollow">https://emergencemachine.com/language-emergent-tool/</a>