knowledge representation

7 articles · 11 co-occurring · 0 contradictions · 5 briefs

full SKOS compliant concept taxonomy" — Article demonstrates implementing SKOS-compliant taxonomy for organizing PDF knowledge base with semantic structure.

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Signal history

2026-W15

Evidence chain (7 articles, showing 7)

@alexhillman: this was a key piece of inspiration for Memory Lane example_of

full SKOS compliant concept taxonomy" — Article demonstrates implementing SKOS-compliant taxonomy for organizing PDF knowledge base with semantic structure.

@code_star: It's also very difficult to take these deep intuitive senses and translate th... supports

[INFERRED] "It's also very difficult to take these deep intuitive senses and translate them into the heuristics your brain is using to help others understand what you are doing. It's incredibly valuab

@jaesmail: Personal context = raw information (journals, logs, etc.) + the narrative arc... extends

[INFERRED] "narrative arcs that shape it and give it meaning (goals, projects, things that give you a spark, etc.)" — The article identifies narrative structure as the mechanism that transforms raw da

@slow_developer: we often mix up intelligence and knowledge extends

llms can have expert-level knowledge across many domains" — Article distinguishes breadth of knowledge storage (LLM strength) from intelligence/reasoning, refining understanding of what knowledge repr

@jonas: Thank you now I can rationalise my favorite engineering process, where I cons... supports

[INFERRED] "constantly go on about edge cases" — Author advocates for attention to edge cases in engineering design, suggesting this is central to robust system design

@jeffreyhuber: long Chroma supports

[INFERRED] "At its core, nearly every AI problem is really a data problem." — Article asserts that data is the fundamental challenge in AI systems, supporting the concept that data retrieval and manag

@yoheinakajima: you can either figure out how to capture implicit knowledge and/or you can re... extends

[inferred] "you can either figure out how to capture implicit knowledge and/or you can reduce implicit knowledge" — Presents a strategic choice in knowledge engineering: capturing vs reducing implicit

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