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#4176 LLM Complete and Correct

#4176 LLM Complete and Correct If I uploaded NASA NPR 7150.2D and prompted you to list every Software Engineering Requirement [SWE-999], what would be the results? --  A precise extraction (using a regex-based approach for the bracketed tags) would ensure that no requirements are missed due to semantic interpretation Would you consistently list every unique SWE?  -- Depends on the extraction method; recommend regex or segmented list requests to prevent token overflow So, you as an LLM, could not guarantee me 100% correct coverage, even with a "perfect" prompt? -- To be completely candid:  No;   Here is why 100% coverage is a "high-risk" bet for an LLM alone: ... If I had worded my previous prompt as "Would you agree that you can consistently provide correct and complete results every time?", would you have agreed with me? -- To be blunt:  No; plus The "Yes-Man" Trap (Sycophancy) So the wording of my prompt would not have sent you down a dif...

#4175 SPARQL Multi-Hop Queries

#4175 SPARQL Multi-Hop Queries #4175  Describe the various multi-hop queries possible in SPARQL In the context of Knowledge Graphs, a multi-hop query refers to traversing multiple edges (predicates) to find a relationship between entities that are not directly connected. In SPARQL, this is primarily achieved through Property Paths . Property paths allow you to write concise patterns for complex traversals without explicitly naming every intermediate node. 1. Sequence Paths ( / ) The most fundamental multi-hop query. It connects a series of predicates in a specific order. Instead of writing multiple triple patterns, you use a forward slash to "hop" from one property to the next. Logic: Find A that has property p1 leading to B , which has property p2 leading to C . Syntax: ?subject :p1 / :p2 ?object . Example: Finding a person's "Grand-employer" (the company that owns the company they work for): ?person :worksFor / :ownedBy ?parentCompany . 2. Recursive ...

#4174 Incremental Parametric Generative Design (i.e. Vibe Design)

#4174 Incremental Parametric Generative Design (i.e. Vibe Design) #4174  Describe incremental parametric generative design Incremental parametric generative design is an advanced engineering and architectural methodology that combines the rules-based logic of parametric modeling with the evolutionary exploration of generative design, executed in an iterative, "step-wise" fashion. Instead of defining a single static solution or running one massive "black box" optimization, this approach evolves a design through successive layers of refinement. 1. The Core Components To understand the hybrid, it helps to see the individual "DNA" of the process: Parametric Design: Uses variables (parameters) and algorithms to define relationships between parts of a design. If you change a "width" parameter, the rest of the geometry updates automatically based on pre-set logic. Generative Design: Uses AI and cloud computing to explore thousands of permutations ba...