Every page write extracts entity refs and creates typed edges (attended, works_at, invested_in, founded, advises) with zero LLM calls.
「零LLM调用」建图是一个关键的工程决策：它意味着知识图谱的构建成本接近零、延迟极低，并且完全可以在每次写入时同步执行。相比之下，依赖LLM提取实体关系的系统必须在延迟、成本和图谱完整性之间做出妥协。这个设计选择也有其代价——纯模式匹配会遗漏需要语义理解才能识别的关系——但对于结构化的[[wiki/people/bob]]风格引用来说，这是正确的权衡。
We observe significant declines in both website visits and question volumes at Stack Overflow, particularly around topics where ChatGPT excels. By contrast, activity in Reddit communities shows no evidence of decline, suggesting the importance of social fabric as a buffer against the community-degrading effects of LLMs.
Conclusion: LLMs cover certain areas that were before solved by human brainpower on stack overflow, and that is measurable over a period of oct-2021 -> march 2023. Reddit does not show this decline and this is alledged due to social fabric on reddit.
I want to know if it is possible to extract claims from this paper automatically in a way that it integrates certain relations in a knowledge graph, utilizing a system that improves itself.
NLTK Spacy Paragraph extraction